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county newsletter
PERFORMANCE ISSUE 2017
COMMUNITY
21st century libraries Page 11
PARKS
Programs & events Page 15
GO GREEN
Recycle room to room Page 25
Spring/Summer 2017
A deeper dive into data Page 26
As stewards of Dakota County tax dollars, the Board of Commissioners uses data to move from ideas to meaningful goals, actions and results to solve problems and seize opportunities that improve the quality of life in Dakota County. In this issue, we share how data helps us provide high-quality services and maintain the metro area’s lowest tax rate and Minnesota’s lowest County property tax per capita. Data is much more than information. It is the foundation of our work to make Dakota County a great place to live, work and play.
Contents Feature Page 26
A DEEPER DIVE INTO DATA Data is an essential tool for positive impact in Dakota County. Take a look behind the numbers to learn more about how we use data to maximize efficiencies, solutions and impact on behalf of Dakota County residents. D E PA R T M E N T S
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Page 7
Page 11
Page 15
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IN BRIEF
OUR WORK
COMMUNITY
PARKS
GO GREEN
We’re helping lowlevel offenders with mental health issues get the services they need to treat their problems and stay out of jail, and it’s saving tax dollars — a winwin for residents.
Learning the skills necessary to earn a stable income, properly manage finances and secure permanent housing is helping young parents get — and stay — on the road to success.
Our libraries do more than lend books. We’re bringing books and technology together to transform the libraries into multiuse 21st century community learning centers.
It’s estimated that nearly 52,000 people visited Whitetail Woods Regional Park in 2015, and that number is expected to grow as the park’s identity and resources grow.
More than 740 people are participating in the County’s first organics collection project in West St. Paul — keeping thousands of pounds of materials out of our landfills.
F O L LOW U S
2 | www.dakotacounty.us | spring/summer 2017
9 KEEPING THE MENTALLY ILL OUT OF JAIL 5 WEATHERING THE STORM 6 DATES FOR YOUR CALENDAR
Closing the gap Helping to keep the mentally ill out of jail
Law enforcement in Dakota County has seen firsthand the negative impact the revolving door of offenders cycling through the criminal justice system can have on families and communities.
spring/summer 2017 | www.dakotacounty.us |
3
In Brief | Keeping the mentally ill out of jail Every year people across the nation who suffer from mental illness spend time in county and city jails without receiving the treatment they need, costing taxpayers billions of dollars. In the more than 3,000 local jails nationwide, 64 percent of inmates suffer from mental illness and 68 percent battle substance abuse. Instead of getting specialized services to treat their mental illness, offenders have traditionally been forced to rely on the criminal justice system for help — something that has proven inadequate and unreliable. The consequences are highly-vulnerable inmates who end up back in jail or cycling through other public systems, and families left feeling broken and hopeless. In Dakota County, additional resources are needed to tackle the issues surrounding the mental health dilemma. About 9 percent of our jail population spends more than a month behind bars, and more than half of those suffer from mental health or chemical dependency issues. About 40 percent of the jail’s operating budget is dedicated to the inmates who stay a month or longer. To break the cycle of incarceration and improve all-around mental health services in law enforcement, the Dakota County Sheriff’s Office and Social Services Department joined ranks with White House. Dakota County was one of 67 city, county and state governments across the nation to first join the White House DataDriven Justice Initiative (DDJ), an effort launched in June 2016 to use data-driven strategies to divert lowlevel offenders with mental illness out of the criminal justice system. As the former White House administration
transitioned, so did the DDJ. Now operating at full force out of the National Association of Counties and with at least 140 jurisdictions participating as of late, Dakota County is one of four Minnesota counties to join the initiative. By signing onto the DDJ, we’re committing to develop de-escalation training and tools for first responders, provide community-based services to high-risk individuals, and use assessment tools to identify low-risk offenders for pre-trial release from jail. First responders often are the first to make contact with a person experiencing a mental health crisis and having the necessary tools can help defuse crisis situations. A special report from the Star Tribune in 2016 revealed that at least 45 percent of people who died in encounters with law enforcement statewide since 2000 had a history of mental illness or were experiencing a mental health crisis. To curtail the number of deaths and improve services, Dakota County and other DDJ communities are creating protocols to battle the problem. Being part of the DDJ also means, Dakota County has access to a wide range of resources, including data
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Dakota County
9
%
of jail population spends more than a month behind bars
of them, more than
50%
suffer from mental health or chemical dependency issues
40
40%
40
40
of jail budget 40
Cost of inmates who stay one month or longer
In Brief | Weathering the storm sharing, diversion and communitybased services assistance, and nationwide research projects. In addition, the DDJ calls for resources to aid veterans with mental-health issues who come into contact with law enforcement and people receiving homeless services.
Always Be Prepared
In order to keep law enforcement and other first responders from being the first line of defense against a mental health crisis, the DDJ is helping Dakota County take steps to link data between the criminal justice and health systems to proactively break the cycle of incarceration. The goal is to identify individuals who have frequent contact with law enforcement and connect them to the appropriate services in the community — reducing the overreliance on emergency health care and encounters with the criminal justice system.
“Be prepared” is not just a Boy Scout motto — it’s a wise model for all of us when it comes to unpredictable weather events, natural disasters or other forms of crisis.
To divert low-risk offenders from jail to mental health and other services, Dakota County is using an objective, data-driven risk assessment tool to identify defendants eligible to be released prior to their criminal case being decided — making sure that low-risk inmates with mentalhealth issues are not left in jail simply because they cannot afford bail. Rather, people are given services to help treat their problems and keep them out of jail in the future. Dakota County and officials nationwide are hopeful taking part in the DDJ will help reduce jail populations, stabilize those suffering from mental illness, better serve communities, and save tax dollars in the process.
Basic items for your hear a warning siren:kithead indoors; emergency turn on the television, radio, computer or smartphone for more information; and take the appropriate action. With a kit in hand, you’ll be ready to weather the storm. Peanut Butter
Water
Dried Fruit
Jerky
Know how to weather the storm
Severe storms, unusually heavy rainfall, flooding and other emergency events have been in the news across the U.S. in recent years. Like many residents in the affected communities, we never think it could happen to us. That’s why it’s important for all of us to plan ahead and prepare for the unexpected. An emergency supply kit is a great place to start. The kit should include basic items you and your family members will need to help you survive for a few days in case emergency help cannot reach you. It’s important that you assemble your kit now since emergencies can strike without warning. Rotate kit supplies when you reset your clock at the start and end of daylight saving time in spring and fall. Your emergency kit should contain food, water and medical supplies that will last for at least 72 hours. In extreme emergencies, basic utilities such as water, electricity, sewer, gas and telephone service might not be available, so your emergency kit also should contain items to help you manage these outages until they can be repaired. When severe weather is in the area, make sure to pay attention to outdoor warning sirens. Dakota County activates warning sirens when wind speeds meet or exceed 70 miles per hour. When you
Three days’ worth, one gallon per person per day
Three days’ worth, of nonperishables
Battery-powered or hand crank emergency radio
Flashlight with extra batteries
Basic items for your emergency kit First aid kit
Extra clothes and blankets
Toiletries
Shoes E
Extra medications for family members who need them
Water
Family Emergency Plan with phone numbers
Pet supplies
Peanut Butter
Dried Fruit
Jerky Three days’ worth, one gallon per person per day
Three days’ worth, of nonperishables
Battery-powered or hand crank emergency radio
Flashlight with extra batteries
First aid kit
Extra clothes and blankets
Toiletries
Shoes E
Extra medications for family members who need them
Family Emergency Plan with phone numbers
Pet supplies
Find a full list at www.dakotacounty.us, search emergency supply kit
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In Brief | Dates for your calendar
Plan on it Know what to do this spring and summer March 14¬April 11
April 22
Master the basics of waste reduction, recycling and composting on Tuesdays, 6–8:30 p.m. at the Dakota County Northern Service Center. www.dakotacounty.us, search Master Recycler.
Celebrate children’s literacy and reading from 10 a.m.–12:30 p.m. at Wentworth Library. www.dakotacounty.us/library, click programs.
March 15
HHW Drop-offs
Master Recycler/Composter
WHEP sign-up Do field and lab research to help monitor the health of County wetlands through the Wetland Health Evaluation Program. www.dakotacounty.us, search volunteers.
March 15¬June 15 Simple Steps
Make walking part of a healthy daily routine with the Simple Steps Walking Program. Free. Open to all who live or work in Dakota County. www.dakotacounty.us, search Simple Steps.
March 18
Fix-It Clinics Get free help repairing broken household items at Pleasant Hill Library from noon–3 p.m. Clinics held monthly around the County. www.dakotacounty, search Fix-It Clinics.
El Día
April¬September Safely dispose of hazardous household waste for free. www.dakotacounty.us, search HHW events. • Saturday, April 29, 9 am–1 pm Cal Ruedy Public Works Building 1225 Progress Drive, Hastings • Saturday, May 6, 9 am–2 pm Lakeville Central Maintenance Facility 7570 179th St. W., Lakeville • Saturday, Sept. 9, 9 am–1 pm Farmington Maintenance Facility 19650 Municipal Drive, Farmington
May 20
Grand opening Spring Lake Park Reserve segment of the Mississippi River Trail, 9 a.m.–noon at Schaar’s Bluff, 8395 127th St. E., Hastings. www.dakotacounty.us/parks, search Mississippi River Trail.
June 3
Grand opening Black Dog segment of Minnesota River Greenway from 10 a.m.–noon at 600 Black Dog Road W., Burnsville. www.dakotacounty.us/parks, search Minnesota River Greenway.
New commissioner Commissioner Joe Atkins was elected in November to succeed retiring Commissioner Nancy Schouweiler in District 4. Joe previously served on the school board and as mayor of Inver Grove Heights. He also served seven terms in the Minnesota House of Representatives.
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Construction updates April–June
County Road 42 — Burnsville Repair bridge over I-35W and extend left turn-lane to northbound I-35W. Two-stage closures: Westbound CR 42: April 17–May 22 Eastbound CR 42: May 22–June 21
April–October
County Road 42/Highway 52 — Rosemount Reconstruct interchange — replace bridges and widen CR 42 to four lanes through the interchange. CR 42 traffic will be detoured.
April–November
County Road 28/63 — Inver Grove Heights Realign and improve to four lanes south of Highway 55 to north of Amana Trail. County road traffic will be detoured.
County Road 86 Reconstruct from CR 47 to Highway 52. CR 86 traffic will be detoured.
July–November County Road 50 — Lakeville Widen CR 50 to four lanes from Dodd Blvd. to Ipava Ave. Traffic will be detoured; access to local businesses will be maintained.
Get project updates online or delivered to your inbox at www.dakotacounty.us, search road construction.
7 HELP FOR YOUNG PARENTS 9 BETTER BRIDGES 10 KEEPING BABIES SAFE
S UP P O RT O P E N D O O D N A P RS HEL
It takes a village New program helps young parents find success
Michaela P., a Dakota County resident, was struggling three years ago when she unexpectedly became pregnant at the age of 19. She was a high-school dropout, unemployed and did not have a stable living situation.
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7
Our Work | Help for young parents
Financial Empowerment Program
246
189
45
Client visits
Clients served in 2016
Families avoided eviction
With a baby on the way and a limited education, Michaela found herself in the alarming position of being unable to provide for her newborn. Facing the possibility of joining the high percentage of teen mothers without a high school degree and struggling to stay employed, Michaela decided to try and make a better life for herself. She learned about a Dakota County program called the Young Parent Grant, which offers parents education opportunities and financial skills, coupled with rent assistance, to equip them with the tools they need to be successful. The focus of the two-year program is to provide young parents the skills to earn a stable income, properly manage finances and secure permanent housing. Participants are required to graduate high school or earn a GED, enroll in college, be employed and attend one-on-one counseling sessions. The program targets parents
who are age 24 or younger and have experienced homelessness or are at risk of becoming homeless. Dakota County partners with community agencies and colleges to offer a comprehensive set of services to get parents through school and into the workforce. The Young Parent Grant served 14 young families since it started in 2015. While providing young parents with rent assistance to have safe homes is central to the Young Parent Grant, the financial counseling services offered through the Dakota County Financial Empowerment Program, also play a huge role in keeping families financially stable. The counseling and training helps parents build assets, decrease debt, repair credit, file taxes and protect resources. It covers everything from balancing bills to managing a checkbook to saving tax returns. Some young parents have never even had a savings account, so teaching
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them how to spend wisely and save efficiently is critical. Although Michaela was ready to make changes in her life, she had to commit to the program and all of its requirements. In order to stay enrolled in the program, she first had to obtain her GED. Once that was completed, Michaela enrolled at Dakota County Technical College, a partner school of the program, to study to be a medical assistant. Financial assistance from the grant allowed Michaela, now a single mother, to move into her own apartment for the first time. While going to school, Michaela also landed a job at a daycare. As she balanced school, work and motherhood, Michaela began to learn the ins and outs of managing her income. As part of the program, she was required to meet with a financial counselor and the work she was doing with her counselor was helping her budget money monthly and pay bills
Our Work | Better bridges
Cross that bridge when you come to it Maintaining better bridge quality in Dakota County
95 Inmates received financial counseling
on time. She even managed to stash away some of her tax return. Along with picking up some essential life skills, Michaela began to carve out a career with the help of the program. She finished her college classes and started an internship with Allina Health. Recently she achieved her goal when she was hired as a medical assistant at a clinic. She credits the program with giving her the structure, resources and inspiration to enter the workforce. In 2016, the Financial Empowerment Program provided 246 service visits and 189 new clients were served. Financial empowerment resources helped 45 families avoid eviction and kept 34 families from losing power. Ninety-five inmates also received financial counseling. Currently, a total of 11 Dakota County families are receiving services from the program.
You’ve probably heard a lot lately about the state of the nation’s public infrastructure. The fact is that every family, every community and every business needs quality public infrastructure to thrive. An important piece of that infrastructure is bridges. We never give much thought to them as we use them, but at Dakota County, we give them the attention they need to keep our transportation system safe.
During the inspection the bridges are rated using National Bridge Inspection Standards. The result? Dakota County bridges have an average sufficiency rating of nearly 96 percent, which is among the highest averages in Minnesota. The County has maintained an average sufficiency rating above the 90-percent target rate for more than five years. Dakota County owns no structurally deficient bridges.
So how does Dakota County stack up with the rest of the state when it comes to bridges? Dakota County owns and maintains 80 bridges on 424 miles of county roads. Each bridge is inspected on a two-year cycle with the exception of new bridges, which are inspected annually for the first five years and the County’s lowest rated bridges, which are inspected annually.
Our “We get you there” promise is our commitment to providing safe and quality roads and bridges that are part of a public infrastructure that you can rely on and be proud of for years to come.
Bridge sufficiency rating 100% 93.5%
92.2%
95.2%
92.2%
95.7%
2011
2012
2013
2014
2015
80
60
40
20
0
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Our Work | Keeping babies safe
A matter of life and death New guidelines for safe infant sleep
Reduce the risk of infant death • Provide a separate space designed specifically for infants to sleep close to the parents’ bed for the first six months to one year. • When feeding during the night, feed baby in bed then place baby in its own separate space to sleep. Using a couch or armchair during feeding increases risk if you fall asleep. • Take along a playpen, play yard or other equipment designed for infants when a crib or bassinet is not available at a caregiver’s home.
From 2012–2015, 11 infants died in Dakota County because of unsafe sleep settings. That’s enough children for a preschool class. Most of these infants were in adult beds sleeping with another person — many with someone under the influence of alcohol or drugs.
neighbor, babysitter. Placing infants to sleep on their tummies, co-sleeping or sharing a bed with an adult, or placing an infant in the care of someone under the influence of alcohol or drugs significantly increases risk of death from suffocation or other causes.
In 2016, the American Academy of Sudden Unexpected Infant Death Pediatrics published new guidelines includes death not only from Sudden to help parents and others Infant Death Syndrome, From create safer settings but also from suffocation, 2012-15, for infants to sleep. The asphyxiation, strangulation 11 infants died guidelines acknowledge and other preventable deaths in Dakota the reality of long wakeful when infants are placed in County nights and sleep-deprived unsafe sleep settings and because of parents and provide positions. At greatest risk unsafe sleep recommendations on how are those infants under four settings. to help reduce the risks of months old and those born unexpected infant death to prematurely or with a low give our youngest and most vulnerable birth weight. the best chance at a healthy start. Sudden Unexpected Infant Deaths can happen to infants in the care For more information on safe sleep of anyone — mom, dad, grandma, guidelines, visit www.dakotacounty.us, search safe sleep. grandpa, aunt, uncle, brother, sister,
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• Designate an alternate caregiver if you or the current caregiver is under the influence of alcohol or drugs.
s Follow the ABCs of safe sleep and instruct all caregivers to follow them as well:
Alone
Place baby alone in a crib for every sleep — never alone on a bed, couch or chair; never with you or anyone else.
Back
Make sure baby is placed on their back and free to breathe.
Crib
Remove all bumpers, pillows, blankets and toys.
7 21ST CENTURY COMMUNITY LEARNING CENTERS
A Poem by
2 4
Hello, Bonjour, Hola, Ciao, Hodi, Namaste, Salaam, OlĂ , Zdras-Tvuy-Te
The new face of 21st century libraries From book lending to learning centers
Books and literacy are and always will be a mainstay at the Dakota County Library, but we’re also doing a lot to meet the changing needs of our 21st century users. Books and technology are bringing together the best of the physical and digital to transform libraries into multiuse community learning centers.
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11
Community | 21st century community learning centers Here, youth, teens and adults can work independently or in groups to imagine, create and achieve through hands-on learning and idea sharing and to explore subjects they may not otherwise experience. The latest digital tools for audio and video production, creative design, photo and film conversion, and 3D innovation are not only enticing young, digitally savvy audiences to the Library, but adults from diverse backgrounds and different fields and levels of expertise are flocking to learn to use them as well. This cuttingedge technology that might be cost prohibitive for most people, is now available, with instruction on how to use it, for free at the Dakota County Library. Along with the latest technology, residents can access the internet from library computers or wireless network
to use robust research and learning tools that can help with everything from kid’s homework to personal and professional skill-building. Many of these powerful tools also make it possible for those who can’t get to the library to access learning online. In-house classes are offered at each of Dakota County’s nine libraries. Program topics cover a range of subjects that appeal to users of all ages and interests — from baby storytimes to senior web surfing, music to theater, taxes to foreign policy, music to art, and much more. Transforming libraries into community learning centers of the 21st century offers everyone a chance to connect, to learn, to be inspired and to succeed in spaces that, because of their proximity to a world of resources, make sense.
Wescott iLAB Digital tools like Mac Pro QuadCore, Final Cut Pro and GarageBand® for audio and video production; iMovie®, Comic Life and Anime Studio creative design tools; and photo, film, and VHS converters are drawing both youth and adults to the Library to learn and exchange ideas and skills on cutting-edge technology in our iLAB Media Suite. For the more artistic spirit, sewing machines, paper and fabric diecutting machines, 3D scanning and printing devices, and other tools in the Creative Suite at the Wescott iLAB are helping crafters bring their innovative ideas to life. Since opening in July, Dakota County residents reserved more than 1,300 hours on the equipment in the Wescott iLAB in Eagan.
Online learning 4,000
Lynda.com hours viewed
600,000
Library internet use in hours
3,500 500,000
3,000
2,500 2,000
2014
2015
2016
400,000
2013
2014
2015
120,000
2013
2014
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2015
This powerful tool offers thousands of highly-rated, skill-building video tutorials on topics from technology and business to job hunting and self-improvement. In 2016, 771 active users watched more than 3,500 hours of instructive tutorials.
Mango Languages
Our world is growing more diverse, so we offer online courses in more than 70 world languages — Spanish, Swahili and Icelandic to name a few — and courses like English for Somali Speakers and Business English for Spanish Speakers. Mobile apps let you learn whenever, wherever you go.
Library in-house program participants 150,000
90,000
2016
Lynda.com
2016
CREATIVE Suite July–Dec 2016 Times used:
247 85 65
MEDIA Suite July–Dec 2016 Times used:
3D printer
Paper cutter
96 59
Audio production station Video production station
Photo, slide, negative converter
In-house classes Starting at birth, kids can enjoy traditional storytimes and music programs and graduate to an assortment of offerings like dancing, reading with dogs, sculpting clay and building circuits. Teens can head to the Library to learn skills like making movies, duct tape art, songwriting and 3D modeling that may not be covered in school. Families can have fun and learn together at Library programs for all ages like Storywalk® in the park, community reading events, poetry contests, and programs on the latest tools and technologies in our Wescott iLAB. Learning isn’t just for kids. Adults will find lots of opportunities to socialize and grow with other adults through book discussions, foreign policy dialogues, music and arts programs, computer and internet training, and much more.
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Community | 21st century community learning centers
Wrap your brain around it Get free instruction on cutting-edge technology and creative tools at the Wescott Library iLAB Register at www.dakotacounty.us/library, click programs.
INTRO TO 3D PRINTING
INTRO TO 3D PRINTING Learn the basics of 3D printing and how to create 3D designs using CAD. • Wed, April 5, 3–3:30 pm OR • Wed, May 3, 6–6:30 pm INTRO TO SEWING AND FABRIC CUTTING Get to know sewing machine basics and how to cut fabric using die-cutter shapes. • Thu, April 6, 6:30–7:30 pm
INTRO TO SEWING AND FABRIC CUTTING
INTRO TO PAPER CUTTING Learn to use the Silhouette Cameo® paper cutter and Silhouette Studio® software. • Mon, April 10, 2–2:30 pm OR • Thu, May 11, 3–3:30 pm AUDIO PRODUCTION 101 Get an introduction to recording and editing audio tracks using GarageBand® for Mac. • Wed, April 12, 6:30–7:30 pm GETTING STARTED WITH GREEN SCREEN AND IMOVIE® Learn video recording basics using a green screen, and importing and editing video using iMovie® for Mac. • Wed, April 19, 6:30–7:30 pm
INTRO TO PAPER CUTTING
PHOTO & FILM DIGITIZATION 101 Learn to restore old photographs and get tips on converting photos, slides, negatives and film to digital formats. • Wed, April 26, 2–2:45 pm OR • Mon, May 8, 6–6:45 pm INTRO TO 3D SCANNING Get an introduction to converting a 3D scan into a 3D printable object. • Wed, May 24, 6–7 pm
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AUDIO PRODUCTION 101
Your Parks
PROGRAMS & EVENTS • SPRING & SUMMER 2017
A BRIGHT FUTURE for Whitetail Woods Regional Park Parks & pints Day camps Grand openings www.dakotacounty.us/parks
FOLL THE FUNOW FACEBOOON K
A bright future Whitetail Woods Regional Park a hit since opening in fall 2014 In fall 2014, Dakota County introduced Whitetail Woods Regional Park to residents, unveiling 456 acres of scenic landscape filled with recreational opportunities in the middle of the county. It was the first time in nearly three decades that a regional park opened in Dakota County. Residents were met with sprawling countryside views, hiking trails around Empire Lake, picturesque overnight camper cabins, a children's
nature play area, gathering areas and more. The park, in Empire Township, also fills a need for residents in communities like Lakeville and Farmington, who previously didn’t have a regional park nearby. Now, more than two years after opening, Whitetail Woods is finding its place among Dakota County’s family of parks. An estimated 52,000 people visited the park in 2015, and those
numbers are expected to trend upward in the future as the park’s identity and resources grow. There has been constant growth for years in the number of people visiting the entire park system. An estimated 1.1 million visitors were recorded in 2015, compared to 879,000 in 2008, according to the Metropolitan Council. Whitetail Woods offers residents diverse recreational opportunities year-
round. The children's nature play area — which consists of water, logs, stumps and other natural items — has been a popular place for families, providing kids with an alternative to the jungle gyms they are accustomed to. The park’s beautiful stone shelter — equipped with a kitchen and seating for large groups — has also been widely used by visitors. Nearly 3,775 people used the shelter at the park in 2016. A summer concert series at the outdoor amphitheater was a success, and a catalogue of programs attracted more than 750 participants. The biggest attraction to Whitetail Woods is the wildly popular camper cabins, perched among dense pine trees in a peaceful section of the park. The overnight cabins, which have won national design awards, are nearly 230-square feet and have a deck, room to sleep 4–6 people, and fire rings. The cabins have been in high demand since the park opened, with hundreds of reservations pouring in just minutes after becoming available to the public. The interest and demand for the cabins has not subsided. The overall occupancy rate for the cabins in 2016
A summer concert series at the outdoor amphitheater was a success, and a catalogue of programs attracted more than 750 participants.
was 82 percent, with 2,455 people visiting the cabins this year. Because of their popularity, we’re planning to build additional camper cabins in the park to help meet the demand. Visitors have also taken advantage of the beautiful natural resources at Whitetail Woods. The park offers scenic hiking trails, and Empire Lake has turned into a premier place for bird and animal watching. Visitors take to the lake to view snapping turtles, migrating birds, eagles and much more.
A big attraction to Whitetail Woods is the wildly popular camper cabins, perched among dense pine trees in a peaceful section of the park.
The place to be in 2016
2,455 Campers
3,775
Picnic shelter users
52,000 Visitors
To continue our commitment to natural resources in the park, nearly 330 acres are expected to be restored in the next few years. The restoration project will include planting prairies and savannas, removing invasive species, and restoring wildland. The goal is to improve wildlife habitat and allow for more diverse vegetation. The future of Whitetail Woods looks bright. To improve and deliver services that enrich the overall parks experience, we’re developing a Parks Visitor Services Strategic Operations Plan. The plan will focus on improving recreation, events, outdoor education, volunteerism, rentals and more. Whitetail Woods will benefit from this plan and the improvement projects, making the park more accessible, offering enhanced recreational opportunities and strengthening its natural resources. The early success and continued growth of Whitetail Woods is providing a great return on taxpayers’ investment in the park system.
PROGRAMS & EVENTS
www.dakotacounty.us/parks Click Programs & Events
River to River Greenway Thompson County Park LILYDALE
BigRivers RiversRegional RegionalTrail Trail Big
MENDOTA
WEST ST PAUL
156 SOUTH ST PAUL
35E MENDOTA SUNFISH HEIGHTS LAKE
Regional Trail Big RiversRiver Minnesota Greenway
494
13
52
3
Spring Lake Park Reserve
56
EAGAN INVER GROVE HEIGHTS
31 43
77
Mississippi River Regional Trail
494
32
55
BURNSVILLE
35E
35W
Lebanon Hills Regional Park
71
38 ROSEMOUNT
APPLE VALLEY
33
52
42
55
NININGER TWP
COATES
46
HASTINGS
85
31
54
47
Dakota Woods Dog Park
9
MARSHAN 316 RAVENNA TWP TWP
62
EMPIRE TWP
23 FARMINGTON
35
42
42
VERMILLION
66 LAKEVILLE
61
VERMILLION TWP
91
Miesville Ravine Park Reserve
50 HAMPTON
Whitetail Woods Regional Park
EUREKA TWP
3
NEW TRIER
HAMPTON TWP
DOUGLAS TWP
50
61
MIESVILLE
20
80
52
56
85
CASTLE ROCK TWP
86
GREENVALE TWP
19
Archery Biking Boating Camper cabin Camping Canoeing/Kayaking
WATERFORD TWP
NORTHFIELD
Cross-country skiing Dog off-leash Dog on-leash Dogsledding Fishing Gardening
RANDOLPH TWP RANDOLPH
88
47 SCIOTA TWP
Lake Byllesby Regional Park
19
Geocaching Hiking Horseback riding Horseshoes Ice skating In-line skating
Kicksledding Mountain biking Nature play Paddleboarding Picnicking Play area
Recreational bonfire Ski skating Sledding Snowshoeing Swimming
Call 952-891-7000 Monday through Friday 8 a.m.–4:30 p.m.
FAMILY FOREVER WILD FAMILY FRIDAY Join us for family fun on the first Friday of every month with park activities and s'mores. Ages: All ages Fee: Free Visitor Center Lebanon Hills Regional Park Nature Bingo Play bingo with a twist during our family-friendly game. Activity Number: 111001-01 • Fri, April 7; 7–8:30 pm Pollinators Explore the world of pollinators, learn how your garden can help them and make seed bombs to take home. Activity Number: 111001-02 • Fri, May 5; 7–8:30 pm Campfire Stories Join us for stories around the campfire with storyteller Roy Edward Power. Activity Number: 111001-03 • Fri, June 2; 7–8:30 pm Scavenger Hunt Join us for a fun nighttime scavenger hunt. Activity Number: 111001-04 • Fri, July 7; 7–8:30 pm Prairies Explore the prairie and learn about its amazing plants and wildlife. Activity Number: 111001-05 • Fri, Aug. 4; 7–8:30 pm Geocaching Use a GPS unit to find hidden treasures in the park. Activity Number: 111001-06 • Fri, Sept. 1; 7–8:30 pm PARENT CHILD CANOE Learn the basics of canoeing and have fun with games and activities on the water. Ages: 5 and older Fee: $10/person Schulze Beach Lebanon Hills Regional Park Activity Number: 110902-01 • Tue, June 13; 6–8 pm Activity Number: 110902-02 • Tue, July 11; 6–8 pm
PARENT CHILD KAYAK Learn the basics of kayaking and have fun with games and activities on the water. Ages: 5 and older Fee: $10/person Schulze Beach Lebanon Hills Regional Park Activity Number: 110901-01 • Tue, June 20; 6–8 pm Activity Number: 110901-02 • Tue, July 18; 6–8 pm PARENT CHILD GEOCACHING Enjoy one-on-one time with your child. Learn how to use a GPS unit to find hidden treasures and what it takes to create a geocache. Ages: 5 and older Fee: $10/person Visitor Center Lebanon Hills Regional Park Activity Number: 112201-01 • Tue, Aug. 8; 6–8 pm PARENT CHILD FISHING Spend time with your child learning about Minnesota fish, how to cast, and practicing catch and release from the pier. Ages: 5 and older Fee: $10/person North Shelter Thompson County Park Activity Number: 111101-01 • Tue, Aug. 15; 6–8 pm WOODCOCK WALK Discover the well-camouflaged woodcock and take a walk to try to spot and hear the bird’s aerial display. Ages: 5 and older Fee: $5/person Visitor Center Lebanon Hills Regional Park Activity Number: 111702-01 • Sat, April 8; 7–9 pm MOTH NIGHT Celebrate National Moth Week. Learn about moths and use lighting techniques to attract and identify them. Ages: 5 and older Fee: $5/person Visitor Center Lebanon Hills Regional Park Activity Number: 111706-01 • Sun, July 30; 8–10 pm MONARCH MIGRATION Learn about the life of a monarch, including its amazing migration. Catch monarchs in the prairie and participate in monarch tagging. Ages: 5 and older Fee: $5/person Visitor Center Lebanon Hills Regional Park Activity Number: 111703-01 • Sat, Sept. 2; 10 am–noon
STORYWALK Take a self-guided walk in the park while reading picture book pages displayed along the trail. Ages: All ages Fee: Free Visitor Center Trailhead Lebanon Hills Regional Park Activity Number: 110902-01 • Fri–Mon, May 26–29; 8 am–8 pm Activity Number: 110902-02 • Fri–Mon, Sept. 1–4; 8 am–8 pm
YOUTH HOMESCHOOL LAB Use the park as your lab for hands-on study, scientific experimentation and recreational skill-building. Ages: 6–12 Fee: $8/person Weather Make observations, collect data and create predictions for the weather around us. Visitor Center Lebanon Hills Regional Park Activity Number: 111501-01 • Wed, April 5; 1–3 pm Frogs and Toads Jump into the world of amphibians and conduct a field survey of the frogs and toads in our park. Visitor Center Lebanon Hills Regional Park Activity Number: 111501-02 • Wed, May 3; 1–3 pm Dragonflies Explore the lives of these aerial predators above and below the water. Visitor Center Lebanon Hills Regional Park Activity Number: 111501-03 • Wed, June 7; 1–3 pm Archery Learn proper technique and range safety and spend time with field target practice at this archery basics course. Archery Shelter Lower Spring Lake Park Reserve Activity Number: 111502-01 • Wed, Sept. 6; 1–3 pm
KNEE-HIGH NATURALISTS Discover nature with a child through hands-on activities, outdoor exploration, art projects, storytime and more. Ages: 3–6 Fee: $8/youth Visitor Center Lebanon Hills Regional Park Quackers Explore the world of ducks and how they waddle and call. Make your own egg art to take home. Activity Number: 112001-01 • Thu, April 13; 10–11:30 am Activity Number: 112001-02 • Sat, April 29; 10–11:30 am Spring Wildflowers Have fun with flowers, play with puppets and costumes, and go on a wildlflower hunt with a naturalist. Activity Number: 112001-03 • Thu, May 11; 10–11:30 am Activity Number: 112001-04 • Sat, May 27; 10–11:30 am Water Fun Learn about water, explore its tiniest critters and paint a watercolor masterpiece. Activity Number: 112001-05 • Thu, June 8; 10–11:30 am Activity Number: 112001-06 • Sat, June 17; 10–11:30 am Turtles and Snakes Explore the world of turtles and snakes, meet our painted turtle and create your own painted turtle art to take home. Activity Number: 112001-07 • Thu, July 13; 10–11:30 am Activity Number: 112001-08 • Sat, July 15; 10–11:30 am Bugs, Bugs, Bugs Dress up like a bug, use a net to catch prairie bugs and learn how important bugs are to our ecosystem. Activity Number: 112001-09 • Thu, Aug. 10; 10–11:30 am Activity Number: 112001-10 • Sat, Aug. 19; 10–11:30 am Tree Tales Learn how trees tell stories, how you can talk to a tree, and explore the different tree parts. Activity Number: 112001-11 • Thu, Sept. 14; 10–11:30 am Activity Number: 112001-12 • Sat, Sept. 23; 10–11:30 am
PROGRAMS & EVENTS SCOUT BADGES Earn your scout badge, petal or adventure in these two-hour programs. Fee: $8/youth Visitor Center Lebanon Hills Regional Park Brownie Girl Scouts — Bugs Badge Learn about insects and catch and examine them close-up. Ages: 6–9 Activity Number: 112302-01 • Sun, Sept. 17; 2–4 pm Junior Girl Scout — Animal Habitats Investigate animal habitats, learn about those that are endangered and what you can do to help protect them. Ages: 9–11 Activity Number: 112303-01 • Sun, Sept. 24; 2–4 pm Bear Cubs — Fur, Feather and Fins Take a hike to learn about endangered species and examine plants as part of your adventure. Ages: 8–9 Activity Number: 112307-01 • Sat, Sept. 23; 2–4 pm Webelos — Into the Woods Learn about the park's ecosystems and the roles animals and plants play in maintaining the ecosystem's health. Ages: 9–11 Activity Number: 112308-01 • Sat, Sept. 30; 2–4 pm SPRING DAY CAMPS Join us during breaks or on school release days for spring day camps. Ages: 8–12 Fee: $30/youth Art in the Park Day Camp Learn about art in nature. Be inspired, create art and take your masterpieces home. Visitor Center Lebanon Hills Regional Park Activity Number: 110414-01 • Mon, April 3; 9 am–3 pm All about Birds Day Camp Explore Minnesota's birds and use a scope and other equipment to observe and identify birds during spring migration. Dakota Lodge Thompson County Park Activity Number: 110414-02 • Fri, April 14; 9 am–3 pm Schaar's Bluff Gathering Center Spring Lake Park Reserve Activity Number: 110414-03 • Mon, April 17; 9 am–3 pm
SUMMER CAMPS SMALL FRY FISH DAY CAMP Join us for a day camp designed for the youngest anglers. Learn the basics of fishing, how to cast, tie knots and get out on the water to catch the big one. Ages: 5–8 Fee: $30/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110407-01 • Fri, June 9; 9 am–3 pm ART IN THE PARK CAMP Discover nature through observation and different art forms, storytelling, games and journals. Ages: 10–14 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110413-01 • Wed–Fri, June 14–16; 9 am–3 pm LITTLE RIPPERS MOUNTAIN BIKE DAY CAMP Join us for a day camp designed for the youngest riders, taught by experts from Valley Bike and Ski. Bring your mountain bike and helmet. No previous experience required. A limited number of rental bikes available. Ages: 6–10 Fee: $30/youth Mountain Bike Shelter Lebanon Hills Regional Park Activity Number: 110406-01 • Wed, June 14; 9 am–noon FISH CAMP Explore Minnesota's fish through hands-on games and activities, and learn to cast and catch and release. Ages: 8–12 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110401-01 • Wed–Fri, June 21–23; 9 am–3 pm BOOKS IN THE WOODS CAMP A camp for our littlest nature explorers who will read and explore the park each day through a different storybook. Ages: 4–6 Fee: $50/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110412-01 • Tue–Fri, June 27–30; 9 am–noon
www.dakotacounty.us/parks Click Programs & Events
NATURE'S MARVELS CAMP Stronger than an ant? Faster than a dragonfly? Bring a cape and test your superpowers against nature's greatest marvels. Ages: 8–12 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110409-01 • Wed–Fri, July 5–7; 9 am–3 pm MOUNTAIN BIKE CAMP Grab your mountain bike and helmet and join the experts from Valley Bike and Ski to learn bike handling skills, bike maintenance, trail maintenance and more. No previous experience required. A limited number of rental bikes available. Ages: 10–15 Fee: $90/youth Mountain Bike Shelter Lebanon Hills Regional Park Activity Number: 110403-01 • Mon–Thu, July 10–13; 9 am–noon Activity Number: 110403-03 • Mon–Thu, Aug. 7–10; 9 am–noon MOUNTAIN BIKE CAMP FOR GIRLS Grab your mountain bike and helmet, and join the experts from Valley Bike and Ski to learn bike handling skills, bike maintenance, trail maintenance and more. No previous experience required. A limited number of rental bikes available. Ages: 10–15 Fee: $90/youth Mountain Bike Shelter Lebanon Hills Regional Park Activity Number: 110403-0 • Mon–Thu, July 10–13; 9 am–noon ARCHERY CAMP Learn the basics of archery, including proper technique, range safety and target shooting. Instructor NASP certified. Ages: 8–12 Fee: $75/youth Archery Shelter Lower Spring Lake Park Reserve Activity Number: 110402-01 • Wed–Fri, July 19–21; 9 am–3 pm PADDLING AND PORTAGE CAMP Learn the basics of canoeing and kayaking, from strokes to equipment to portaging, and get out on the water to practice your new skills. Ages: 10–14 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110410-01 • Wed–Fri, July 26–28; 9 am–3 pm
MYTHICAL CREATURES CAMP Investigate the truth behind Minnesota's creature myths and create some of your own. Ages: 8–12 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110411-01 • Wed–Fri, Aug. 16–18; 9 am–3 pm ULTIMATE HIKER CAMP Explore the trails and learn how to prepare for a hike, how to stay safe and basic wayfinding. Have fun with challenges, scavenger hunts and more. Ages: 10–14 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110408-01 • Wed–Fri, Aug. 23–25; 9 am–3 pm WILDERNESS SURVIVAL CAMP Learn to survive in the woods by constructing survival shelters, building fires, learning knot-tying skills, wayfinding and more. Ages: 8–12 Fee: $75/youth Visitor Center Lebanon Hills Regional Park Activity Number: 110404-01 • Wed–Fri, Aug. 30–Sept. 1; 9 am–3 pm
ADULT WILD ART Join us to create natureinspired art. Ages: 16 and older Fee: Free, registration required Wet Felted Eggs Join the Textile Center in creating vibrant colored eggs. Roll, tap and squish your favorite colors of wool into shape with warm water and soap. A Minnesota Legacy program. Dakota Lodge Thompson County Park Activity Number: 110201-01 • Sat, April 1; 9–11 am Clay Art — For the Birds Join Artistry and create a bird sculpture and a bird house or bird feeder out of clay to learn basic ceramic handbuilding techniques. A Minnesota Legacy program. Schaar's Bluff Gathering Center Spring Lake Park Reserve Activity Number: 110201-02 • Sat, May 13; 9 am–noon
Call 952-891-7000 Monday through Friday 8 a.m.–4:30 p.m. FLY FISHING WORKSHOP Join the Fly Fishing Women of Minnesota for an in-depth introduction to fly fishing, casting techniques and fly tying. Ages: 16 and older Fee: $30/person Visitor Center Lebanon Hills Regional Park Activity Number: 111102-02 • Tue, April 11 & 18; 6–8 pm HIKE THE PARKS: WILDFLOWER WALK Take a hike when the spring ephemerals are in full bloom and learn basic wildflower identification. Ages: 16 and older Fee: $8/person Trailhead Miesville Ravine Park Reserve Activity Number: 111403-01 • Sat, April 29; 1–3 pm BIRDING AND BIKING Learn about the birds along the Spring Lake Park Reserve segment of the Mississippi River Trail. Bring your bike and helmet. Scope and binoculars provided. Ages: 16 and older Fee: $18/person West Shelter Spring Lake Park Reserve Activity Number: 111707-01 • Sat, May 6; 8–10 am BIRDING ON THE MISSISSIPPI Explore the Rock Island Swing Bridge and its unique vantage point of the Mississippi River while learning birding tips. Binoculars provided. Ages: 16 and older Fee: Free, registration requested Swing Bridge Park Shelter Mississippi River Regional Trail Activity Number: 111701-01 • Sun, May 7; 8–10 am BIRDING AT LAKE BYLLESBY Explore the mudflats of Lake Byllesby, classified by the Audubon as an Important Bird Area. Equipment and shuttle provided. Ages: 16 and older Fee: $8/person Lakeside Shelter Lake Byllesby Regional Park Activity Number: 111708-01 • Sun, May 7; 6–8 pm
PARKS AND PINTS: THE LORE OF LEBANON HILLS Join experts from the Dakota County Historical Society as they share stories about the area that is now Lebanon Hills Regional Park. Bring your own bottle of beer or wine. Participants will receive a commemorative pint glass. Pre-registration required. Ages: 21 and older Fee: $8/person Visitor Center Lebanon Hills Regional Park Activity Number: 111602-01 • Fri, May 12; 7–8:30 pm INTRO TO FLY FISHING FOR WOMEN Get a hands-on introduction to fly fishing taught by the Fly Fishing Women of Minnesota. Ages: 16 and older Fee: $15/person Visitor Center Lebanon Hills Regional Park Activity Number: 111102-01 • Sat, May 13; 10 am–noon BACKYARD AGRICULTURE: BEEKEEPING BEYOND THE BASICS If you keep bees, this is the class for you. JoAnne Sabin will share more about bee behavior, hive management, equipment, the latest on bee health, swarms and simple queen rearing. Prerequisite: Beekeeping Basics and past experience keeping bees. Ages: 16 and older Fee: $30/person Visitor Center Lebanon Hills Regional Park Activity Number: 111301-01 • Thu, June 8 & 15; 6–9 pm EDIBLE MUSHROOM WORKSHOP Join instructors Sarah Foltz Jordan and Nick Jordan in taking mushrooming to the next level. Activities include identification, a foray in the woods, photo presentations, cooking and sampling. No previous experience required. Ages: 16 and older Fee: $60/person Camp Sacajawea Lebanon Hills Regional Park Activity Number: 111709-01 Sun, Aug. 27; 11 am–5 pm
NEED EQUIPMENT? Rent paddleboards, canoes and kayaks at the Lebanon Hills Visitor Center.
www.dakotacounty.us/parks, search equipment rental
ADULT DAY CAMPS Enjoy learning new recreation skills while experiencing the great outdoors. Mountain Bike Camp for Women Learn mountain biking skills from Valley Bike and Ski. Topics include bike handling skills, equipment, safety, trails and more. For all skill levels. Limited number of demo bikes available for use. Ages: 14 and older Fee: $40/person Mountain Bike Shelter Lebanon Hills Regional Park Activity Number: 110415-01 • Wed, June 14, 21 & 28; 6–8 pm Mountain Bike Camp for Men Learn the basics of mountain biking with experts from Valley Bike and Ski. Topics include bike handling skills, equipment, safety, trails and more. For all skill levels. Limited number of demo bikes available for use. Ages: 14 and older Fee: $40/person Mountain Bike Shelter Lebanon Hills Regional Park Activity Number: 110415-02 • Wed, June 14, 21 & 28; 6–8 pm Wilderness Survival Camp Learn to survive in the woods by constructing survival shelters, building fires, learning knot tying skills, wayfinding and more. Ages: 16 and older Fee: $40/person Visitor Center Lebanon Hills Regional Park Activity Number: 110416-01 • Sat, Aug. 12; 9 am–1 pm
Backwoods Recreation Explore the park and learn the basics of archery and how to navigate with a GPS unit. Ages: 16 and older Fee: $40/person Archery Shelter Lower Spring Lake Park Reserve Activity Number: 110416-02 • Sat, July 22; 9 am–1 pm
EVENTS MISSISSIPPI RIVER TRAIL GRAND OPENING Ages: All ages Fee: Free Schaar's Bluff Gathering Center Spring Lake Park Reserve • Sat, May 20; 9 am–noon TAKE A KID FISHING Spend quality time with a child. Bring your own pole or borrow one of ours. Learn to fish, practice knot tying, casting, baiting a hook and more. Ages: All ages Fee: Free North Shelter Thompson County Park Activity Number: 110801-01 • Sun, June 11; noon–3 pm MUSIC IN THE PARKS Bring a blanket or chair and picnic dinner and enjoy outdoor musical performances. Ages: All ages Fee: Free Empire Shelter Whitetail Woods Regional Park Activity Number: 112601-01 • Sat, June 24; 6–7:30 pm Activity Number: 112601-02 • Sat, July 29; 6–7:30 pm Activity Number: 112601-03 • Sat, Aug. 26; 6–7:30 pm
INFORMATION REGISTRATION To register online, search for the program using the activity number or a key word in the program title. Registration is not required for free programs unless noted. Satisfaction is guaranteed. PAYMENT Payment is due at registration. All major credit cards are accepted. IF WE NEED TO CANCEL Cancellations posted at www.dakotacounty.us/parks.
IF YOU NEED TO CANCEL Refund policy is posted at www.dakotacounty.us/parks, click Programs & Events. SCHOLARSHIPS Call 952-891-7000. ACCESSIBILITY At least three weeks before the program, tell us what accommodation would make the program accessible to you or your family. EQUIPMENT Provided unless specified.
Rent an adventure Lebanon Hills Regional Park Open daily, May 27–Sept. 4 www.dakotacounty.us/parks, search equipment rental
23 ORGANIC SUCCESS 25 ROOM TO ROOM RECYCLING
Getting the drop on organics Organics collection pilot increases understanding and education
Dakota County is collecting about 2,000 pounds of organic material every week as part of a pilot project that helps the County understand the demand and barriers for residents recycling food scraps, napkins and paper towels. It is also educating residents on the importance of organics recycling.
Spring/summer 2017 | www.dakotacounty.us |
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Go Green | Organic success The project started in October 2016, when the County began accepting residential organics at a drop site at Thompson County Park in West St. Paul. More than 740 people registered to participate in the project — well above the goal of 200 — with more than 150 people signing up in the first two days alone. Prior to the drop site opening, nearly 150 participants attended one of two information sessions at the Wentworth Library to get an overview of the project and information on organics recycling. Instead of putting food waste and soiled paper in their trash at home, participants are dropping these items off at the drop site. The organic material is brought to a commercial
compost facility in Rosemount where it is turned into compost in as little as 45 days. Compost has great benefits, including holding more moisture than soil, which reduces erosion. It also has a high nutrient content, which limits the need for chemical fertilizers.
The compost industry also benefits our local economy, providing more than 250 full-time and part-time jobs as well as an estimated 200 seasonal jobs in Minnesota. The organics drop site complements other County efforts to reach the
More than
8,000 pounds of organic material collected each month in Dakota County — as much as two cars
Drive up. Drop off. Do good. UCosoekdingPaOintsil Ouldg LKailpetorp B
24 | www.dakotacounty.us | spring/summer 2017
Go Green | Room to room recycling state-mandated 75-percent recycling goal by 2030. In 2017, the County will continue to offer the drop site for residents to recycle their organic waste.
Raising the rates
Going room to room can help you recycle more
During this project, Dakota County is focusing on residents within two miles of the park, but all County residents are eligible to participate.
Kitchen:
Residents can sign up by calling 952-891-7557 or emailing organics@co.dakota.mn.us. Participants receive a guide on recycling organics and free compostable bags.
Home office:
Juice, milk and soup cartons; cans; glass food jars; plastic bottles; and plastic jugs.
Mail, notebooks, magazines, and office and school paper. Staples, Dakota Dakota County residents and County waste recycled labels and stickers do not businesses recycled 49 percent of have to be removed. their waste in 2015 — down 3 percent from 2014. How can weGOAL do ofbetter and 75% by 2030 Bathroom: achieve the state’s goal of a 75-percent Boxes from toothpaste and recycling rate by 2030? 52% 54% 54% 52% 49% medications; empty bottles First, we need to understand the from shampoo, lotion and reason for the decline. One reason for mouthwash. our lower recycling rate is we’re not recycling everything we can. In fact, Laundry room: according to a Minnesota Pollution Boxes from dryer sheets, Control Agency study, about 30 laundry detergent and percent of what we throw away can softener bottles. be collected in home recycling carts.
2011 2012 2013 2014 2015
For more information, go to www.dakotacounty.us and search organics recycling drop off.
D
Need paint, cleaners and yard chemicals? Check the Reuse Shelf for free products.
www.dakotacounty.us, search Recycling Zone A nominal fee is charged for televisions, monitors and tires.
Surprisingly, there’s a lot of paper and plastic containers being tossed in the trash. This material ends up sitting in a landfill or burned in an incinerator instead of being made into new, useful products. Recycling in every room of the house gives us a much better chance to increase recycling and reduce our trash. Start simple by collecting more in the kitchen and adding one or two rooms to your recycling set-up. Learn what other household items you can recycle — in your curbside recycling program or at local drop-off locations — at www.dakotacounty.us, search Green Guide.
Dakota County waste recycled
GOAL of 75% by 2030
52% 54% 54% 52%
49%
2011 2012 2013 2014 2015
From cooking oil, pesticides and household cleaners to laptops, vacuums and aluminum foil, you can recycle more than you think for free at The Recycling Zone.
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Data objectively tells us how we’re doing. Measuring data helps identify how programs or initiatives can have an impact in other areas of the County. Learning from and leveraging data helps make life easier for residents, Rated Dakota County Parks or good from clearing congestion at anexcellent intersection to reducing waste to helping homeless families gain safe shelter.
96%
Data also helps us achieve efficiencies that save taxpayers money. For example,
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The task of discovering groups and structures in the data that are in some way or another "similar", without using
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
How much did we do? 80
The task of generalizing known structure to apply to new data.
Benefits of data Providing a more compact representation of the data set, including visualization
Results validation and launch effectiveness
50
25%
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40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data
How well did we do it? 25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
50%
75%
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0
Benefits of data
25%
Providing a more compact representation of the data set, including visualization
Results validation and launch effectiveness
2012 2011
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The task of generalizing known structure to apply to new data.
50
100
Searches for relationships between variables. For example, a supermarket might gather data on customer
20
efficient, effective services, data playsfor a major Library Launchpad tablets added kids role in how we operate. Collecting and analyzing data informs strategic decisions on the types of services we provide, where capital improvement investments are made, how to identify potential cost savings and much more. The task of discovering groups and structures in the data that are in some way or another "similar", without using
Searches for relationships between variables. For example, a supermarket might gather data on customer
110 100
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When it comes to providing residents with 2011
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
2012
110
Results validation and launch effectiveness
50
2013
40
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
2014 2016
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The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
2015
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
90
110
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2014
30%
2009
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
100
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2015
3.3
22%
Fall
2015
2014
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30%
120
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
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18 16
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17
2015
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3.3
22%
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
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County vehicles with monitors
28 | www.dakotacounty.us | spring/summer 2017
TC#347545948
Are Dakota County residents better off? in-vehicle monitoring systems were recently installed on more than 250 County vehicles. The systems provide data on fuel usage, mileage, driving behaviors, idling vehicles, maintenance, seat belt use and more. Applying this data makes the County fleet more efficient, leading to a cost savings of approximately $170,000 annually. This and other data initiatives ultimately lead to significant cost savings every year. Providing efficient services has allowed us to maintain the lowest property tax levy per capita in the state. Dakota County also has the lowest levy per household with residents paying $834, compared to a metro average of $1,295. This means a typical family saves several hundred dollars a year on County services here, compared with other places in the region.
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$170,000 Approximate fleet cost savings annually
50%
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40 30
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The task of generalizing known structure to apply to new data.
80
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10
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12 17
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30 20 10 0
2013
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2016
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4.5
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8.6
18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
8.6
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20
2015 2014
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2013
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2009
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30%
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IMPROVING PUBLIC SAFETY 2011
2011
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
Almost every aspect of policing and improving public safety in Dakota County involves data. It drives a majority of strategic decisions within the Sheriff’s Office, including where to position deputies, how to prevent traffic crashes, and when to expand the force. Reviewing the quantities and types of calls for service influences how deputies help keep communities in a 350-square-mile jurisdiction safe. Such data also helps identify needs for special services, such as a recent partnership with the U.S. Marshals to apprehend high-level felony offenders. Crash data, used regularly, impacts traffic enforcement and campaigns, which helped lead to an 8 percent crash reduction through September of 2016. There were 147 total crashes in September 2016, compared to 160 in September 2015. 90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
2015
2015
2014
2014 2016
2016
2013
2013
2012
2012
30%
Searches for relationships between variables. For example, a supermarket might gather data on customer
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
110 100
2009
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
Results validation and launch effectiveness
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
50 40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data 25%
50%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
75%
NC#67833
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Benefits of data
25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
50%
75%
NC#67833
TC#347545948
Data also has a positive impact on crime victims. To combat domestic violence and a rise in electronic crimes, a forensic analyst was hired through a grant to help analyze cell phone data in cases involving harassment and L I B R A R Y protection L I B R A R Y orders. The analyst’s work makes it easier for law L I B R A R Y enforcement to extract cell phone data, which leads to more evidence for prosecutors. As a result, the conviction rate in the domestic violence-related cases has increased from 51 to 94 percent.
Cost savings Cost savings
Intake and digital data are also used at the county jail, which housed an average of 224 male offenders per day Building more efficiently Building more efficiently in 2016. For example, intake data collected helped lead Building more efficiently to the addition of a mental health coordinator position. This new coordinator will work collaboratively with social services staff on strategies to support inmates in need of mental health services, as well as developing a plan for success once they are released. Corrections supervisors are equipped with body cameras that can be used to record incidents involving the use of necessary force or other incidents where there may be a need to better document inmate and staff interactions.
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spring/summer 2017 | www.dakotacounty.us |
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3.3
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2009
Results validation and launch effectiveness The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
9.3
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
2019
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18% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
50
Discovered structures & visualization
11%
Results validation and launch effectiveness
40
The extraction of patterns and knowledge from large amounts of data
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75%
Summer
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
50
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25%
75%
The computational process of discovering patterns in large data sets involving methods at the intersection of
22%
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
55%
Justification Process 25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
40 30
16
The extraction of patterns and knowledge from large amounts of data
25%
18
18
The computational process of discovering patterns in large data sets involving methods at the intersection of
50
Benefits of data mining
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and
11%
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16
of artificial intelligence, machine learning, statistics, and database
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18
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17 16 18 16 Benefits of data mining
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and
16 12
50%
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25%
55%
Justification Process 25%
50%
25%
75%
The extraction of patterns and knowledge from large amounts of data
2013
2014
75%
2015
2016
2017
2018
of artificial intelligence, machine learning, statistics, and database
11% 18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
2019
8.6
9.3
computer science.
2015
2015
2014
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3.3
22%
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2016
2013
2013
2012
2012
30%
Searches for relationships between variables. For example, a supermarket might gather data on customer
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
110 100
2009
2009
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
25%
50%
75%
18 17 16 18 16
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2%
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2013
2014
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
75%
2015
2016
2017
D E E P E R
2018
Summer
Fall
22%
Discovered structures & visualization
11% 18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
8.6
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
The extraction of patterns and knowledge from large amounts of data
The computational process of discovering patterns in large data sets involving methods at the intersection of
Summer
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
Discovered structures & visualization
11%
8.6
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
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The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
Fall
Winter
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2013
2016
2013
2009
2009
2012
2012
30%
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
10
HELPING RESIDENTS THRIVE
100 90 80
2012
2011
2011
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
110
2013
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
The task of discovering groups and structures in the data that are in some way or another "similar", without using
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data 25%
50%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
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The State Demographer’s Office projects Dakota County will be home to more than half a million people by 2035 compared to about 417,000 residents today. The County is becoming more diverse and the current population is aging. The number of Dakota County residents older than 65 is expected to double between 2005 and 2035. As our County continues to grow, so will needs of its most vulnerable residents, including those experiencing homelessness, physical disabilities and mental illness. The identification of unusual data records, that might be interesting or data discrepancies that require further
100
Results validation and launch effectiveness
30 20
2014 2016
2009
2012
30%
120
2013
Searches for relationships between variables. For example, a supermarket might gather data on customer
50 40
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
2015 2014
2009
110
50
2014
2014 2016
120
Results validation and launch effectiveness
2015
2015
3.3
22%
Winter
2015 2016
3.3
The computational process of discovering patterns in large data sets involving methods at the intersection of
I N T O 18% D A4.5 T A
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
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2019
D I V E
The computational process of discovering patterns in large data sets involving methods at the intersection of
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55%
Justification Process 25%
The computational process of discovering patterns in large data sets involving methods at the intersection of
The identification of unusual data records, that might be interesting or data discrepancies that require further
Benefits of data
25%
50%
75%
Searches for relationships between variables. For example, a supermarket might gather data on customer
Results validation and launch effectiveness
50
The task of discovering groups and structures in the data that are in some way or another "similar", without using
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
TC#347545948
40 30
The task of generalizing known structure to apply to new data.
Benefits of data
Providing a more compact representation of the data set, including visualization
25%
50%
20
75%
10 0
Results validation and launch effectiveness
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
L I B R A R Y
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Integrated information systems help identify residents who are in need of specific help and resources, such as people experiencing a housing crisis or needing social services. Assessment data entered into the systems creates a centralized intake and helps case workers match the most appropriate services for a person’s needs. More than 1,025 living situations were assessed from November 2014 to September 2016 using the coordinated entry system for housing. Data collected from surveys helps identify the best ways to help people experiencing homelessness in Dakota County. In 2016, a one-night count of unsheltered individuals revealed 63 people who either stayed up all night or slept in vehicles, doorways or elsewhere outdoors. Another count found an average of 50 people were turned away from a shelter for lack of space. Such survey data led us to work with a coalition of faith communities to open temporary emergency shelters during severe winter temperatures, serving at least 71 people in need. Cases of residents with disabilities who want more integrated housing and employment options were recently reviewed. The 2016 review was part of a state plan to give better opportunities to people with disabilities. Of the 230 cases reviewed, 75.6 percent of case plans addressed residents’ employment goals and 80.2 percent addressed their housing goals. These numbers showed our case plans have a high overall level of compliance with the state. However, despite the review showing positive outcomes, our goal is to improve the number of plans that address residents’ employment and housing goals by 10 percent in 2017.
63 Cost savings
A one-night count of unsheltered Building efficiently people inmore Dakota County
2015
2015 2014
2016
2014 2016
2013
2009
2013
2009 2012 2011
O P E N
to
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W E L C O M E
200571to2035 People older served by emergency shelters Population than 65 will double by 2035
80% Of 230 cases addressed housing goals
30 | www.dakotacounty.us | spring/summer 2017
Incr
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40 30
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
10
22% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
Benefits of data
20 25%
50%
75%
Results validation and launch effectiveness
12 17
20
16
10 50%
45%
22% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
22%
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
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The extraction of patterns and knowledge from large amounts of data
30 20 10 0
The extraction of patterns and knowledge from large amounts of data
2013
2014
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
75%
2015
2016
2017
2018
Summer
NC#67833
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0
8.6
4.5
18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
8.6
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2014 2016
EFFICIENTLY IMPROVING BUILDINGS 2013
2013
2009
2012
2011
2011
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
A sizable portion of the money we spend goes towards County property improvements, which are part of a larger capital improvement budget including roads, parks, trails and County bridges. In 2017, $132 million is budgeted for Dakota County’s Capital Improvement Program. Data collection and analysis are critically important to ensuring these projects are prioritized and designed efficiently and provide a good return on the taxpayers’ investment. 90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
50%
2016
2013
2013
2012
2012
30% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
Searches for relationships between variables. For example, a supermarket might gather data on customer
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
110 100
2009
Results validation and launch effectiveness
50 40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data 25%
50%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
75%
NC#67833
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NC#67833
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For example, it was determined in 2015 that the Judicial Center building in Hastings needed a renovation due to our growing population, crime trends and the number of court cases being filed. No new court space had been added since the building opened in 1989. The cost of the renovation was first estimated at $24 million. We commissioned a study that included extensive research and data collection, a look at how the court rooms were being used, and the number of cases filed. The study showed we could meet our service needs at the Judicial Center through 2030 with two smaller additions to the building. The project was completed on time and under budget in November 2016 at a cost of $10.6 million. Data collection and analysis while planning the project saved $13.4 million and an additional $6 million in operating costs through 2030. We also track things at the County jail like growth in the number of expected inmates, alternative housing options, and operation costs to ensure taxpayer money isn’t wasted. Adding one cell block in the County jail is estimated to cost more than $15 million. Based on data tracking and study, the County has not had to construct new jail space since 2005, saving millions of taxpayer dollars. Libraries are a major asset for residents and require capital improvements to remain relevant and useful. Data — such as populations served at each site, the number and types of books checked out, and public and staff surveys — is reviewed to determine the optimal way to design and renovate libraries. Reviewing this data allows staff to identify efficient ways to use space, like designing multipurpose rooms, which leads to substantial cost savings. This data assessment process is currently being used to guide the upcoming Galaxie Library renovation.
20 10 0
Judicial Center estimated renovation cost
$24 million 2012 2011
Study Judicial Center
$10.6 million Final renovation cost
L I B R A R Y
Cost savings In building multi-purpose rooms
spring/summer 2017 | www.dakotacounty.us |
25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
40 2015
2014
2012
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
2014
2014
30
2009
30%
2015
2015 2016
Winter
2015 2016
3.3
computer science.
2009
Results validation and launch effectiveness The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
9.3
3.3
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
2019
Fall
18% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
50
Discovered structures & visualization
11%
Results validation and launch effectiveness
40
50%
25%
75%
The computational process of discovering patterns in large data sets involving methods at the intersection of
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
50
55%
Justification Process 25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
40 30
16
The extraction of patterns and knowledge from large amounts of data
25%
18
18
The computational process of discovering patterns in large data sets involving methods at the intersection of
50
Benefits of data mining
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and
11%
22%
0
16
of artificial intelligence, machine learning, statistics, and database
31
50%
75%
NC#
12
machine learning, statistics, and
22%
18
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
17 16 18 16 Benefits of data mining
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and
16 12
50%
45%
25%
55%
Justification Process 25%
50%
25%
75%
The extraction of patterns and knowledge from large amounts of data
2013
2014
75%
2015
2016
2017
2018
of artificial intelligence, machine learning, statistics, and database
11% 18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
2019
8.6
9.3
computer science.
2015
2015
2014
2014 2016
3.3
22%
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2016
2013
2013
2012
2012
30%
Searches for relationships between variables. For example, a supermarket might gather data on customer
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
110 100
2009
2009
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
25%
50%
75%
18 17 16 18 16
50%
45%
A
2%
patterns and arge amounts of data. patterns and arge amounts of data.
The extraction of patterns and knowledge from large amounts of data
The computational process of discovering patterns in large data sets involving methods at the intersection of
The extraction of patterns and knowledge from large amounts of data
The extraction of patterns and knowledge from large amounts of data
2013
2014
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
75%
2015
2016
2017
D E E P E R
2018
Summer
The computational process of discovering patterns in large data sets involving methods at the intersection of
Fall
22%
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
Discovered structures & visualization
11% 18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
8.6
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
100 90 80
8.6
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
Winter
2016
2016
2013
2009 2012
2012 2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
2013
2009
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
2012
2012
2011
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
The identification of unusual data records, that might be interesting or data discrepancies that require further
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data
Results validation and launch effectiveness
25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
50
50%
75%
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The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
30 20
2014 2016
2013
110
50
2014
2013
2009
30%
120
Results validation and launch effectiveness
2015 2014
3.3
22%
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2015 2014
2011
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
Fall
2015
IMPROVING ROADS AND PREVENTING ACCIDENTS
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
110
Discovered structures & visualization
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2009
30%
120
Summer
I N T O 18% D A4.5 T A
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
Winter
2015 2016
3.3
The computational process of discovering patterns in large data sets involving methods at the intersection of
11%
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
The extraction of patterns and knowledge from large amounts of data
2019
D I V E
The computational process of discovering patterns in large data sets involving methods at the intersection of
%
al process of erns in large data sets ds at the intersection gence, machine s, and database
50%
25%
75%
The extraction of patterns and knowledge from large amounts of data
10 0
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Benefits of data
25%
50%
75%
Searches for relationships between variables. For example, a supermarket might gather data on customer
Results validation and launch effectiveness
50
The task of discovering groups and structures in the data that are in some way or another "similar", without using
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
TC#347545948
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Roads in the County are used by thousands of residents and their families every day. That’s why it’s a high priority to make sure our roads are maintained and operated in a safe manner.
STOP
We turn to traffic data to ensure intersections are designed as safely and efficiently as possible. Currently, nearly 60 side-stop or all-way-stop locations within the county are being monitored for different traffic control, such as a traffic signal or roundabout. Measurements include traffic volume, and the number, rate and severity of collisions. Analyzing this traffic data helps identify intersections or roads that could be improved, and the best type of improvement to make each location safer for motorists and pedestrians.
60
30
The task of generalizing known structure to apply to new data.
Benefits of data
25%
Providing a more compact representation of the data set, including visualization
50%
20
75%
10 0
Results validation and launch effectiveness
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
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TC#347545948
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A recent example of this work occurred at the intersection of Oakdale Avenue and Wentworth Avenue in West St. Paul. Data shows that 9,000 vehicles travel daily through the all-way-stop intersection. Sixty-seven percent of all crashes at the intersection are dangerous right-angle crashes, suggesting the intersection is at capacity and drivers are having trouble identifying who has the right of way. Data assessment helped the County determine that a roundabout should be constructed to improve traffic flow and reduce the risk of serious injury or fatal crashes. A one-night count of unsheltered
63
Intersections being monitored Loren ipsum folor sit amet, consectetur adipiscing elit, sed do eiusmod tempor.
Wentworth Ave
The computational process of discovering patterns in large data sets involving methods at the intersection of
55%
Justification Process 25%
The computational process of discovering patterns in large data sets involving methods at the intersection of
The identification of unusual data records, that might be interesting or data discrepancies that require further
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Oakdale Ave
67% Of crashes were right-angle
people in Dakota County Another intersection, County Road 46 and Buck Hill Road
and Kenyon Avenue in Burnsville, was also assessed due to the number of crashes and traffic volume. The intersection had an increase of crashes in 2014 and 20 crashes overall in the last three years. The crash rate — which considers the number of crashes and traffic volume — was well above the state average for side-stop intersections. Data analysis made the case for a traffic signal to be constructed at this O P E N W E LC O M E site in 2017. 2015
2015
2014
2016
2013
2009
2014
2016
2013
2009
2012
2011
2012
2011
If placed at the wrong location, traffic signals and other types of traffic controls can quickly become safety hazards. That’s why relying on sound traffic data and analysis of traffic control options by professional traffic engineers is important to providing safe, efficient traffic control.
71
People served by emergency shelters
32 | www.dakotacounty.us | spring/summer 2017
9,000 Vehicles daily. Determined a roundabout would reduce the risk of fatal injuries
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
40 30
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
10
22% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
Benefits of data
20 25%
50%
75%
Results validation and launch effectiveness
12 17
20
16
10 50%
45%
22% The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
22%
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
The computational process of discovering patterns in large data sets involving methods at the intersection of
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
The extraction of patterns and knowledge from large amounts of data
30 20 10 0
2013
The extraction of patterns and knowledge from large amounts of data
2014
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
75%
2015
2016
2017
2018
Summer
NC#67833
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0
2019
Fall
18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
18%
4.5
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
8.6
The extraction of patterns and knowledge from large amounts of Data. The extraction of patterns and knowledge from large amounts of data.
2013
2009
2012
2011
2011
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
Data isn’t usually at the top of residents’ minds when they use our parks and libraries. However, data helps determine how we maximize the user experience for these very popular destinations, which attract almost 3 million visitors annually. 90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
25%
50%
75%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
NC#67833
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Dakota County Library tracks circulation numbers for books and other materials as well as waiting lists for popular items. A total of 4,650,298 items were checked out of our libraries in 2016. Staff uses the data to determine when waiting lists grow too long and additional items must be purchased. For example, data shows Launchpad computer tablets for children are highly popular. Over eight months, 135 tablets were checked out 3,573 times. This data led to 72 tablets being added to library branches, which gives many more children access to the educational tools. A recent analysis of wireless internet usage at our libraries revealed the need to expand wireless service at all branches, which was recently completed. The computational process of discovering patterns in large data sets involving methods at the intersection of artificial
2013
2016
2013
2012
2012
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
The identification of unusual data records, that might be interesting or data discrepancies that require further
110
Searches for relationships between variables. For example, a supermarket might gather data on customer
100
The task of discovering groups and structures in the data that are in some way or another "similar", without using
Searches for relationships between variables. For example, a supermarket might gather data on customer
The task of discovering groups and structures in the data that are in some way or another "similar", without using
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
Benefits of data
2011
2011 The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
110 100
2009
Results validation and launch effectiveness
50 40 30 20 10
90
The task of generalizing known structure to apply to new data.
80
Providing a more compact representation of the data set, including visualization
0 Benefits of data 25%
50%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
75%
NC#67833
Systematic
Responsive
Dominion
Turning to parks, the 2016 residential survey showed 96 CHECKED AVAILABLE percent ofOUT participants rated the park system as excellent or good. Using data for long-term planning, maintenance and natural resource management is essential to maintaining these high-quality resources for residents.
72 more
Data from scientific surveys and public meetings help gauge residents’ needs and refine master plans. Mapping Library Launchpad added kids vegetation, data plays a vital roletablets in restoring and for managing helping to control invasive species and planning long-term projects. Keeping inventory of all maintenance services and facilities establishes a standard that helps us keep costs low and get the most out of our work. The computational process of discovering patterns in large data sets involving methods at the intersection of artificial
CHECKED OUT
Systematic
Responsive
Dominion
AVAILABLE
96% 72 more
Rated Dakota County Parks excellent or good Library Launchpad tablets added for kids
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OUTCOME-BASED ACCOUNTABILITY 0
We use data-driven decisions and disciplined thinking to improve the lives of children, families and entire communities for the long term. It’s a philosophy that’s known as Outcome Based Accountability (OBA). Through it, we first learn from residents what is most important to them as it relates to quality of life in the county. Then we determine how and where our services can contribute most positively to residents’ priorities. Using the OBA approach, we ask these three questions about everything we do: How much did we do? How well did we do it? And are Dakota County residents better off? Reviewing answers to these questions helps us to identify opportunities and strategies for improvement in providing the most value possible to Dakota County residents.
The measurement How much did we do? How well did we do it? Are Dakota County residents better off?
Using this data-driven approach to determine and deliver services is not only beneficial for residents, it also helps us continually learn and improve. Having a coordinated, comprehensive approach can also result in outcomes being achieved more quickly, and it measurement increases transparencyThe and accountability for the wellbeing of communities.
How much did we do? As Minnesota’s third-largest county, Dakota County has substantial demands for a variety of services. Data and our use of it is critical to making choices that generate the best possible results and use precious resources to How well did we doresponsibly it? make life better today and tomorrow in Dakota County. Are Dakota County residents better off?
spring/summer 2017 | www.dakotacounty.us |
25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
20
2014 2016
ENHANCING PARK AND LIBRARY EXPERIENCES 2013
The extraction of patterns and knowledge from large amounts of data. The extraction of patterns and knowledge from large amounts of data.
120
2014
2014
40 2015
2014
2012
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
2015
2015 2016
2009
30
2009
30%
computer science.
Winter
2015 2016
3.3
9.3
30%
Results validation and launch effectiveness The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.
9.3
8.6
3.3
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
50
Discovered structures & visualization
11%
Results validation and launch effectiveness
50
50%
25%
75%
The computational process of discovering patterns in large data sets involving methods at the intersection of
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
40
55%
Justification Process 25%
The identification of unusual data records, that might be interesting or data discrepancies that require further investigation.
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database
40 30
16
The extraction of patterns and knowledge from large amounts of data
25%
18
18
The computational process of discovering patterns in large data sets involving methods at the intersection of
50
Benefits of data mining
The computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and
11%
22%
0
16
of artificial intelligence, machine learning, statistics, and database
33
50%
75%
NC#
Get involved Know what's happening and what you can do to play a part in Dakota County government • Give input at open houses • P articipate in surveys • S erve on committees • A ttend commissioner meetings • V olunteer time • I nteract on Facebook or Twitter • S ign up for e-newsletters www.dakotacounty.us #dakotacountygovernment
34 | www.dakotacounty.us | spring/summer 2017
Your Commissioners Mike Slavik District 1
T: 651-438-4427 Includes the cities of Coates, Farmington, Hampton, Hastings, Miesville, New Trier, Randolph, Vermillion, Northfield Precinct 2; townships of Castle Rock, Douglas, Empire, Eureka, Greenvale, Hampton, Marshan, Nininger, Randolph, Ravenna, Sciota, Vermillion and Waterford.
Kathleen A. Gaylord District 2
T: 651-438-4428 Includes the cities of South St. Paul, West St. Paul, Sunfish Lake, and Inver Grove Heights Precincts 1 and 8–10.
Front row: Kathleen A. Gaylord, Mike Slavik (Chair), Thomas A. Egan Back row: Mary Liz Holberg, Chris Gerlach, Liz Workman, Joe Atkins LILYDALE
Thomas A. Egan
MENDOTA
District 3
T: 651-438-4429 Includes the cities of Lilydale, Mendota, Mendota Heights, and Eagan Precincts 1–7 and 9–12.
MENDOTA HEIGHTS
T: 651-438-4430 Includes the cities of Inver Grove Heights Precincts 2–7; Eagan Precincts 8 and 13–17; and Rosemount Precincts 1–2, 4, and 6–7.
Liz Workman District 5
T: 651-438-4431 Includes the city of Burnsville.
2
EAGAN INVER GROVE HEIGHTS
BURNSVILLE
5
APPLE VALLEY
4
7 ROSEMOUNT
District 7
T: 651-438-4411 Includes the cities of Rosemount Precincts 3 and 5, and Apple Valley.
HASTINGS
COATES
EMPIRE
1
LAKEVILLE FARMINGTON
RAVENNA MARSHAN
VERMILLION TWP
NEW TRIER
MIESVILLE
HAMPTON
District 6
Chris Gerlach
NININGER
VERMILLION
6
Mary Liz Holberg T: 651-438-4243 Includes the city of Lakeville.
SOUTH ST. PAUL
SUNFISH LAKE
3
Joe Atkins District 4
WEST ST. PAUL
EUREKA
CASTLE ROCK
HAMPTON TWP
DOUGLAS
RANDOLPH TWP RANDOLPH SCIOTA
GREENVALE
WATERFORD NORTHFIELD
spring/summer 2017 | www.dakotacounty.us |
35
LET YOUR IMAGINATION SOAR
Discover high-tech gadgets to create projects of all kinds. Scan and print in 3D Produce and edit audio and video Digitize film Scan and edit photos
Design with state-of-the-art software Die-cut paper and fabric Sew And more…
www.dakotacounty.us/library, search iLAB