Successfully reported this slideshow.
SDS Knowledge Portal<br />
Complexities of spatial decision making<br />Spatial decision making faces various decision complexities such as<br /><ul>...
Complex multi-dimensional and heterogeneous data describing decision situations;
Large or extremely large data sets that include data in numerical, map, image, text, and other forms;
Large number of available alternatives or a need to generate decision alternatives "on the fly" according to the changing ...
Multiple participants with different and often conflicting interests;
Multiple categories of knowledge involved, including expert knowledge and layman knowledge.</li></ul>http://geoanalytics.n...
Definition of Spatial Decision Support (SDS)<br />Spatial decision support is the computational or informational assistanc...
Body of Knowledge in SDS<br />Status of the field of SDS<br /><ul><li>Active field of research and practice
Vast amount of information/knowledge on spatial decision support
Countless publications on decision process, methods, etc.
Large numbers of SDS resources (e.g. tools) developed for all kinds of applications, many for specific project needs</li><...
Easy access of SDS resources and understanding of their functionalities</li></ul> Need for Spatial Decision Support Knowl...
SDS Knowledge Portal<br />Objectives<br /><ul><li>Identify the structure underlying the body of knowledge on SDS, e.g.
Common workflows during decision making process
Common set of methods associated with specific stepsof these workflows during a decision process
Tools that implement a particular method
Organize/structure the body of knowledge in SDS on the Portal
Establish a standardized terminology within a user community
Facilitate access of SDS Resources
Help improve the quality of decision making</li></li></ul><li>SDS Knowledge Portal<br />Approach<br />Develop a common org...
Hierarchies/graphs, with each concept defined by
Name, synonyms, acronyms/abbreviations  (  standard vocabulary)
Upcoming SlideShare
Loading in …5
×

Spatial Decision Support Portal- Presented at AAG 2010

520 views

Published on

A presentation prepared for the American Association of Geographers (AAG) 2010 Annual Meeting in Washington DC. The presentation discusses work done by the University of Redlands and the SDS Consortium to organize and provide access to the body of knowledge regarding Spatial Decision Support

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Spatial Decision Support Portal- Presented at AAG 2010

  1. 1. SDS Knowledge Portal<br />
  2. 2.
  3. 3. Complexities of spatial decision making<br />Spatial decision making faces various decision complexities such as<br /><ul><li>Spatial nature and temporal development of phenomena and processes;
  4. 4. Complex multi-dimensional and heterogeneous data describing decision situations;
  5. 5. Large or extremely large data sets that include data in numerical, map, image, text, and other forms;
  6. 6. Large number of available alternatives or a need to generate decision alternatives "on the fly" according to the changing situation;
  7. 7. Multiple participants with different and often conflicting interests;
  8. 8. Multiple categories of knowledge involved, including expert knowledge and layman knowledge.</li></ul>http://geoanalytics.net/VisA-SDS-2006/<br />
  9. 9. Definition of Spatial Decision Support (SDS)<br />Spatial decision support is the computational or informational assistance for making better informed decisions about problems with a geographic or spatial component. This support assists with the development, evaluation and selection of proper policies, plans, scenarios, projects, interventions, or solution strategies. <br /> Spatial Decision Support Consortium, 2008<br />
  10. 10. Body of Knowledge in SDS<br />Status of the field of SDS<br /><ul><li>Active field of research and practice
  11. 11. Vast amount of information/knowledge on spatial decision support
  12. 12. Countless publications on decision process, methods, etc.
  13. 13. Large numbers of SDS resources (e.g. tools) developed for all kinds of applications, many for specific project needs</li></ul>The Need<br /><ul><li>Systematic organization/presentation of the body of knowledge in SDS
  14. 14. Easy access of SDS resources and understanding of their functionalities</li></ul> Need for Spatial Decision Support Knowledge Portal<br />
  15. 15. SDS Knowledge Portal<br />Objectives<br /><ul><li>Identify the structure underlying the body of knowledge on SDS, e.g.
  16. 16. Common workflows during decision making process
  17. 17. Common set of methods associated with specific stepsof these workflows during a decision process
  18. 18. Tools that implement a particular method
  19. 19. Organize/structure the body of knowledge in SDS on the Portal
  20. 20. Establish a standardized terminology within a user community
  21. 21. Facilitate access of SDS Resources
  22. 22. Help improve the quality of decision making</li></li></ul><li>SDS Knowledge Portal<br />Approach<br />Develop a common organizational conceptual framework– using ontologies, containing<br /><ul><li>SDS related concepts, organized into
  23. 23. Hierarchies/graphs, with each concept defined by
  24. 24. Name, synonyms, acronyms/abbreviations (  standard vocabulary)
  25. 25. Description,
  26. 26. Set of formally defined attributes
  27. 27. Set of formally defined relations to other concepts</li></ul>The content of the SDS Portal is formalized<br /> it can be queried easily<br />
  28. 28. SDS Knowledge Portal<br />Incremental development of the SDS portal<br />Knowledge<br />Portal<br />- User accessing knowledge about SDS, learning about decision process, methods, etc.<br />Resource<br />Portal<br />- User seeking resource info: tools, models, data sources, case studs, literature, etc<br />Solution<br />Portal<br />- User seeking resource recommendations for their specific decision problem solution<br />
  29. 29. Current status of the SDS Knowledge Portal<br /><ul><li>Establishment of the SDS Consortium
  30. 30. Developed a conceptual framework for the body of knowledge in SDS
  31. 31. Systematically classified various SDS resources
  32. 32. Established a standard set of terms
  33. 33. Developed the SDS Knowledge Portal
  34. 34. Public release in April 2009
  35. 35. 2 incremental new releases since then, with one coming up soon</li></li></ul><li>Current status of the SDS Knowledge Portal<br />The SDS Conceptual framework includes > 800 concepts with natural language definition as well as formally defined logical relations among the concepts, describing <br /><ul><li>Spatial decision problem types
  36. 36. Decision contexts
  37. 37. Knowledge domains and application domains
  38. 38. Decision process phase and steps
  39. 39. Methods and techniques
  40. 40. Various resources including tools and models, data sources, case studies, etc.</li></li></ul><li>Current status of the SDS Knowledge Portal<br /><ul><li>~ 100 methods and techniques
  41. 41. > 80 SDS tools and models
  42. 42. > 20 data sources
  43. 43. > 20 data models
  44. 44. 8 decision process workflow templates
  45. 45. > 20 case studies
  46. 46. > 600 literature references
  47. 47. > 40 related websites</li></li></ul><li>The conceptual framework is coded in description logic (OWL web ontology language):<br /><ul><li>Flexible enough for capturing the hierarchical as well as associative relations among concepts
  48. 48. Rigorous enough for automatic consistency checking of the conceptual framework
  49. 49. Enables semantic query with inferencing to derive implicit knowledge</li></li></ul><li>
  50. 50. Current status of the SDS Knowledge Portal<br />The way information is organized on the Portal by ontologies facilitates information retrieval on the Portal. The user can :<br /><ul><li>Browse the conceptual hierarchy
  51. 51. Follow the hierarchical structure in the ontologies
  52. 52. Follow the relation links from concept to concept
  53. 53. Search for a concept in the ontologies
  54. 54. Browse resources (literature, SDS tools and models, case studies, data sources, data models, etc.) Multiple ways of browsing, e.g. for tools:
  55. 55. Browse by name
  56. 56. Browse by decision problem types
  57. 57. Browse by decision process steps
  58. 58. Browse by application domain
  59. 59. Browse by knowledge domain
  60. 60. Etc.
  61. 61. Search tools or case studies with multiple search criteria (concept search)
  62. 62. Search literature – conventional bibliographical and full text keyword search, as well concept search.</li></li></ul><li>Ongoing research on SDS Knowledge Portal<br /><ul><li>Further addition to the Portal content, especially in the areas of
  63. 63. Decision process workflows
  64. 64. Relationship between decision problem types and methods
  65. 65. Collaboration decision making methods and tools
  66. 66. SDS resources
  67. 67. Supporting users in solving their decision problems:
  68. 68. Include more relevant SDS resources
  69. 69. Improve browse/search functionality on the Portal for solution resources
  70. 70. Portal makes recommendation on solution resources
  71. 71. User case studies inform the Portal development
  72. 72. Work towards tools/models interoperability</li></li></ul><li>Ongoing research on SDS Knowledge Portal<br /><ul><li>Further addition to the Portal content, especially in the areas of
  73. 73. Decision process workflows
  74. 74. Relationship between decision problem types and methods
  75. 75. Collaboration decision making methods and tools
  76. 76. SDS resources
  77. 77. Supporting the user in solving their decision problems:
  78. 78. Include more relevant SDS resources
  79. 79. Improve browse/search functionality on the Portal for solution resources
  80. 80. Portal makes recommendation on solution resources
  81. 81. Clients case studies inform the Portal development
  82. 82. Work towards tools/models interoperability</li></li></ul><li>User input<br />From reasoning<br />
  83. 83. User input information about their specific decision problem<br />
  84. 84. User input information about their specific decision problem<br />
  85. 85. The Portal runs an inferences engine based on<br /><ul><li>Existing information on the Portal
  86. 86. A set of inferencing rules (implemented with SPARQL)</li></li></ul><li>The portal derives a subset of SDS resources that may be applicable for the user’s decision problem, and recommend them to the user.<br />
  87. 87. Ongoing research on SDS Knowledge Portal<br /><ul><li>Further addition to the Portal content, especially in the areas of
  88. 88. Decision process workflows
  89. 89. Relationship between decision problem types and methods
  90. 90. Collaboration decision making methods and tools
  91. 91. SDS resources
  92. 92. Supporting the user in solving their decision problems:
  93. 93. Include more relevant SDS resources
  94. 94. Improve browse/search functionality on the Portal for solution resources
  95. 95. Portal makes recommendation on solution resources
  96. 96. Clients case studies inform the Portal development
  97. 97. Work towards tools/models interoperability</li></li></ul><li>More efforts towards promoting tools interoperability/chaining<br />The tools now have finer grained definitions in terms of:<br /><ul><li>The type of decision problems they address
  98. 98. The steps/tasks during the decision process they support
  99. 99. The knowledge domains they model
  100. 100. The modeling/calculation method they implement
  101. 101. The application domain they are used in
  102. 102. As well as other properties related to their analysis scale, input/output requirements, systems requirement, and other general descriptions</li></li></ul><li>Questions?<br />Nathan StroutNaicong LiRedlands InstituteUniversity of Redlandsnathan_strout@spatial.redlands.edunaicong_li@spatial.redlands.eduhttp://www.spatial.redlands.edu/sdshttp://www.spatial.redlands.edu/redlandsinstitute<br />

×