1. Spatial databases: Introduction Geog 495: GIS database design

2. Outlines Decoding the acronym GIS GIScience view on spatial database DBMS view on spatial database Review questions

3. 1. Decoding the acronym GIS GI Systems GI Sciences GI Services Evolution of GIS

4. GI Systems Geographic information system (GIS) is a system for input, storage, manipulation, and output of geographic information (NCGIA CC) Database system designed to handle geographically referenced data Composed of data, software, hardware, people and procedure (ESRI)

5. GI Sciences The science behind the technology Aimed at enhancing knowledge of geographic concepts and their computational implementations seeks to redefine geographic concepts and their use in the context of geographic information systems Dedicated to the development and use of theories, methods, technology, and data for understanding geographic processes, relationships, and pattern (UCGIS 1994)

6. GI Services Gradual shift from centralized GIS to distributed GIS Examples include location-based service, Web- mapping, Web-based planning support system GIService is miniature, mobile, public, and task- specific If GISystem is data-centered, GIService is person-centered

7. Evolution of GIS GIScience view Database view GISystem GIScience, Database GIServices technology research

8. 2. GIScience View Overcoming limitations of existing GISystem Challenges Needs Subjects of GIScience

9. Challenges Because progress has historically relied on a fragmented gathering of approaches inherited from cartography, imposed by hardware, or borrowed from other computer-related fields, we are faced with the current situation in which increased functionality has characteristically been accompanied by increased conceptual complexity, making GIS progressively more nonintuitive for the user. Representations of space and time by Donna J. Peuquet, 2002

10. Needs Need better ways to represent, understand, manage, and communicate our natural world

11. Subjects of GIScience How people think about geographical space and time –Ontology of geographic kind How to translate human conceptualizations into formalisms that allow these processes to be repetitively consistent –Formalism of spatial language How to make people interact more naturally with information systems –System design Egenhofer et al, 1999

12. Further readings on GIScience Goodchild, M.F., 1992, Geographical information science. International Journal of Geographical Information Systems 6(1): 31- 45 Goodchild M.F., 1997,What is Geographic Information Science?, NCGIA Core Curriculum Unit #2 http://www.ncgia.ucsb.edu/giscc/units/u002/ Mark D., 1999, Geographic Information Science: Critical issues in an emerging cross-disciplinary research domain, workshop on Geographic Information Science and Geospatial Activities at NSF http://www.geog.buffalo.edu/ncgia/GIScienceReport.html

13. 3. Database System View Overcoming limitations of existing DBMS Challenges Needs Evolutions of DB systems GIS architecture SDBMS architecture Subjects of spatial databases

14. Challenges Previous DBMS is not well accommodated into geographic concepts as most of commercial DBMS are designed to handle attribute data What’s special about geographic?  go to the next slide

15. Properties of geographic data Has location –Location is a special kind of key (i.e. list of values) how is it handled? Multidimensional –Directional, topological relationships, how is it formalized Scale-dependent –Spatial versus Geographic Its occurrence is spatially autocorrelated –Tobler’s first law of geography Not well captured by precise description –Uncertainty should be formalized Some geographic phenomena are continuous –Object-view wouldn’t fit well Some geographic phenomenon is closely associated with temporal changes –event, process, moving object Geographic data need special treatment indeed!

16. Needs We need more constructs to handle spatial information in order to reduce the semantic gap between the user’s view of spatial data and the database implementation Spatial Database: a Tour by Shashi Shekhar and Sanjay Chawla, 2003

17. Evolution of DB system File systems Network DBMS Hierarchical DBMS Relational DBMS Object-oriented DBMS Object-relational DBMS

18. What is object-Relational DBMS? Add OO-ness to tables All persistent (database) information is still in tables, but some of the tabular entries can have richer data structure, that is ADTs ORDBMS supports an extended form of SQL Potential for mapping spatial concepts For example, Oracle 8i implements spatial data types and spatial operators

19. GIS architecture Built upon File system + Relational DB –Spatial data is stored in file system –Attribute data is stored in tables –Separation between non-spatial and spatial data –Specific module for spatial data management –Also called georelational model –Examples: Arc/Info, MGE, TiGRis (Intergraph)

20. GIS architecture Built upon relational DB –Spatial/non-spatial data are stored in tables –Storing spatial data in table is tedious –Can hinge on SQL –Violate data independence principle –Bad performance –Difficulty in defining new (spatial) types

21. GIS architecture Built upon object-oriented DB –Can define user-defined data type (e.g. ArcGIS geodatabase has different data models such as hydrology, network, land parcel, and so on) –Can define user-defined operations –Can inherit properties and operations from superclass

22. How to map land parcel data? In relational database –e.g. arc/info coverage, arcview shapefile –spatial data is stored in a file and it’s linked to attribute data through common attributes In object-oriented database –e.g. arcgis geodatabases –you can inherit properties from object, featureclass, polyline and call the methods area() defined in polyline

23. Spatial DBMS Special kind of DBMS that are specifically designed to handle spatial data Usually seen as middleware (e.g. ArcSDE) Can be implemented in either thick or thin client (e.g. CGI versus Java) Have different capabilities depending on which database models Usually support spatial indexing, efficient algorithms for spatial operations, and domain- specific rules for query optimization

24. Architecture of SDBMS

25. Subjects of spatial databases Spatial taxonomy Data model Query language Query processing File organization and indices Query optimization Data mining

26. Review questions Discuss the differences between spatial and nonspatial data How can object-relational databases be used to implement an SDBMS? Compare and contrast –GIS vs. SDBMS –OODBMS vs. ORDBMS –GI Systems vs. GI Services –Querying vs. Data mining