I have worked for the Wisconsin DNR for about 10 years. I manage data on Wisconsins 15,000 lakes, program databases and develop web pages. My background.

Volunteers participating statewide

•Tables with Rows and Columns•Tables are Connected

Station ID

Station Name Latitude Longitude

133320 Lake Wingra - Center

43.055 -89.415

133083 Wingra Creek – Olin Avenue

43.052 -89.383

133081 Wingra Creek – Beld Street

43.049 -89.394

Station ID Station Name Latitude Longitude

133320 Lake Wingra - Center 43.055 -89.415

133083 Wingra Creek – Olin Avenue 43.052 -89.383

133081 Wingra Creek – Beld Street 43.049 -89.394

Station ID Date Monitored

Data Collectors

133320 6/15/2005 Joe Smith

133320 7/1/2005 Judy Jones

133320 7/20/2005 Joe Smith

Station ID

Station Name Date Monitored

Data Collectors

133320 Lake Wingra - Center

6/15/2005 Joe Smith

133320 Lake Wingra- Middle

7/1/2005 Judy Jones

133320 Wingra Lake - Center

7/20/2005 Joe Smith

1997-1999

•Paradox and Microsoft Access. •Reports not yet online. •Repetition of information in tables.

2000

•Oracle Database. •Reports and volunteer data entry online. •Non-generic tables and columns.

Secchi_feet Did Disk Hit Bottom?

Water Color

9 No Green

12.25 No Green

14 No Blue

2007

•Oracle Database. •Reports and volunteer data entry online. •Tables and Columns Reusable

Parameter Result Units

Secchi Depth 14 Feet

Hit Bottom? No

Water Color Blue

Stream Flow 144 Cfs

# of Zebra Mussels on Plate 100

Who: PeopleWhere: Monitoring StationsWhy: ProjectsWhen: Date/TimeHow: Methods and Equipment

Who: PeopleWhere: Monitoring StationsWhy: ProjectsWhen: Date/TimeHow: Methods and Equipment

One More?

Who: PeopleWhere: Monitoring StationsWhy: ProjectsWhen: Date/TimeHow: Methods and EquipmentHow Good: Quality Assurance Steps Taken

•Flowages•Seepage Lakes•Drainage Lakes•Spring Lakes•Drained Lakes

• Databases should be well organized, but generic enough to accommodate a variety of information

• Metadata should always be recorded along with the data, to assure repeatability 20, 50, 100 years from now.

• Metadata should include “How Good?” Quality assurance information to help prove that the data is good.

• Our lakes are dynamic, diverse and ever-changing. Our database must be up to the task of adapting to changes (new aquatic invasive species) in data we collect.

• Reports and map products should be automated as much as possible to enable people to get up-to-date data fast, when needed.