GIS and Spatial Data Management Explained

1. GIS and Spatial Data Management Explained Corey Tucker Tamarack Geographic Technologies

2. Who are you? • You are IT professionals who have • Some experience with GIS • Exposed to it through a project • Being used in your organization • Want to know more • Heard of GIS • Part of a new project • Exposed to it by friends or colleagues in the business • Not really not sure what it is, but you know it has something to do with maps

3. Outline • Look at some GIS examples • Review what GIS is • Geographic Data • Analysis • Visualization • Review common IM issues for GIS • Answer questions

4. Examples of GIS in Action • Showcase from ESRI • Newfoundland and Labrador Geoscience Resource Atlas • Map of Population Change

5. Who uses GIS? • Geographers in many roles • Natural Resource Management Professionals • Land Managers • Mining and Energy Sector Management & Exploration Professionals • Business Analysts • Social Science Professionals

6. What Skills are Required? • Under-graduate degree focused on geomatics or GIS • MUN, McGill, UNB, St. Mary’s, most universities • Masters in Geography, with focus on GIS • MUN, McGill, UofT, most major universities • Advanced Diploma in GIS or Geomatics • CNA, College of Geographic Sciences, MUN, BCIT, Sir Sanford Fleming

7. What is GIS? • Geographic Information System • Collection of hardware and software for the capture, storage, display and analysis of spatially referenced data Geographic Database GIS Analysis and Geoprocessing Visualization & Interpretation

8. Geographic Data • Comes in two flavors Vector Raster

9. Geographic Data • Each point, line or polygon represents a real world feature • Town, road, forest stand, county, etc

10. Geographic Data • Each feature can have many attributes • Population, name, species, etc • Each attribute is a column in a database table

11. Geographic Data • Raster data consists of pixels • Common spatial extent • Single value • Multiple values for the same extent can be stored as a multiple bands in one raster dataset

12. Geographic Data • Each point is stored as a coordinate in space • Geographic • Latitude, Longitude • Spherical • Projected • X,Y • Planar (Flat)

13. Geographic Data • Several ways to create vector data • Digitizing • Scanning • Conversion from raster • Raster data comes from many sources • Remote sensing • Computer models • Scanning

14. Geographic Data • Spatial data can be HUGE in size • One raster dataset representing St. John’s, with a resolution (pixel size) of 30 CM is several GB • Collections are now TB in size, soon to be PB • Vector data is smaller, but as data is captured at better resolutions, size grows • Dataset containing all the roads in Newfoundland and Labrador is 100 MB

15. Geographic Data • Data may be stored in a spatial database… • Extended relational database, such as Oracle or MS SQL Server • Enterprise GIS (many users making changes) • Expensive • Or in a proprietary vendor format • Local dataset for single user update • Cheap

16. Geographic Data • Why create and maintain all of this spatial data? This costs a fortune! • Improve operational efficiency • Know where everything is • Know how to get there • Plan for better resource use • See the world in ways previously not possible • Where do layers intersect? • What patterns exist?

17. GIS Analysis • Process of modeling the world • Derive new data from existing data using analytical tools • Results require visualization and interpretation • Geoprocessing describes the environment used to derive new data • An orchestration of functions, where the result of one feeds input into the next • Automation is critical

18. GIS Analysis

19. GIS Analysis • Analytical models can create fantastic amounts of data • Organizations should understand nature of GIS work • Data storage requirements • Back-up procedures for results • Ad-hoc nature of GIS project development

20. GIS Analysis • Process for determining what can reliably be seen from a point

21. GIS Analysis

22. GIS Visualization • A map is a very powerful medium for • Data Integration • Data exploration • Who does not appreciate a good looking map? • 2-D and 3-D • Google Earth, Microsoft Virtual Earth

23. GIS Visualization • Maps have moved from paper to digital form • Google Maps, PDF • Move to internet mapping has revolutionized GIS • Maximizes exposure of data investment • Requires specific enterprise IT and GIS skills • Governments are investing in spatial data infrastructure (SDI) to support this paradigm shift

24. GIS Visualization • The push to put spatial data onto the web has exposed many IM issues • Currency • Quality • Confidentiality • Ownership • Documentation (metadata) • Standards

25. Data Currency • Most GIS data is not static • Regular updates occur • Copies of originals proliferate through an organization • Typically undocumented • Analysis results may be invalid unless the latest data is used • What’s the best source?

26. Data Quality • All GIS data has some level of error • Measurement Device • Human • Processing • Relevant scale of data should dictate its use • 1:250 000 roads may be 10 – 50 m from reality • People trust digital data as truth • Limitations of data must be understood prior to use

27. Data Confidentiality • Most GIS data does Not contain personal or private data • Vast majority of GNL data is freely available to the public • But some does • Tap water sampling locations • Location of a crime • Often times data owner does not appreciate the sensitivity of the data they have

28. Data Ownership • Source of data is often times unknown • Department of origin may be known, but a point of contact is typically not • Custodial ownership is typical, but regularly not understood • Base map data may originate at the federal level and be passed to the province • Lack of metadata propagates the problem

29. Data Documentation • Known as metadata • Everyone understands its importance, but no one does it (unless made to) • Many standards exist • FGDC, ISO and all their various profiles • No standard exists for Newfoundland and Labrador • Some departments author metadata to support data sharing initiatives

30. Data Documentation • Solutions to many of the issues with GIS data hinge on the use of metadata • Critical to adopt a standard and start using it • Avoid the religious wars and getting buried in the details • Better to start as simply as possible and grow capacity

31. Data Standards • Standards for data collection and maintenance make life easier • Map projection, metadata, column name, feature description, resolution • Typically focused on a department or agency • Corporate standards require inter-departmental cooperation, which is hard • Without standards duplication of effort proliferates

32. Data Standards • Example: Provincial Streets Dataset • Several departments, agencies require an up to date street layer • Dept. of Transportation & Works • Dept. of Env. & Conservation, Surveys and Mapping Division • Dept. of if Finance, NL Statistics Agency • Dept. of Municipal Affairs • Royal Newfoundland Constabulary

33. Data Standards • What standards are needed? • Road name (All upper case or start with a capital?) • Road type (Road or Rd, Ave or Av?) • Address range model (Left/Right, From/To) • Community (Recorded or not?) • Resolution (1:1000 or 1:10 000?) • Precision (Accurate to < 1 m or < 5 m?) • Currency (Quarterly or annual update?)

34. Data Standards • Is everyone working together? • Who ultimately decides what standards are adopted? • How is the cost of creating and maintaining the data covered? • Single department bears the expense or is it cost-shared?

35. What is GNL doing? • Plan to implement an SDI • Corporate Map Resource Center (Summer 2009) • Application for upload of department data to a central repository • Searchable metadata • Service based • Automated

36. Thank-you Questions?