The Ontology Project

1. The Ontology Project Boots Cassel Active members of the committee: Gordon Davies Rich LeBlanc Andrew McGettrick Heikki Topi

2. If I seem a bit distracted … 50 Democrats + Independents 49 Republicans VA still unsure, but Dem leading

3. Back on subject • The Project • An Ontology of all of the Computing and Information related subject areas • Who • Sponsored by the US NSF, ACM, IEEE-CS with participation and interest from a number of people from this side of the ocean.

4. A Problem? • Our discipline is young, and growing fast • Experts are independently defining and exploring various portions of the discipline • These portions may overlap. • There may be portions that are missed, at least for a time.

5. An opportunity? • Because it is still relatively early in the life of the computing disciplines • It may still be possible to coordinate the development and dissemination of knowledge about the various parts • It may still be possible to keep the experts aware of each other’s work • Avoid unnecessary duplication • Be aware of missing pieces

6. What do we need? • A complete representation of the entirety of the discipline • In all its component parts • In all its manifestations • This representation • Must be dynamic, responding to changes as they occur • Must be easily accessible to all who can use it.

7. What do we have to work with? • The ACM Computing Classification System • A very important listing of the topics in the computing discipline • First system produced in 1964 • Total 191 entries, including repeated “general” and “miscellaneous” • Current system dated 1998, updated in 2006 • Lists topics, including subtopic relationships and a few “isRelatedTo” connections

8. More to work with • The curriculum documents • Produced by various societies: • ACM, IEEE-CS, AIS, IFIP • Australian Computer Society • German Accreditation for Informatics Programs • British Computer Society • Etc. • Topics listed from the perspective of educational needs • Relationships include • Core educational requirements • Topics that support learning outcomes • Topic dependencies

9. Too much of a good thing? • The lists from the various organizations are not consistent, nor are they complementary • Overlap • Contradict • In some cases, even between different publications of the same groups! • What is a conscientious curriculum developer supposed to do?

10. An Example • An area that appears in most curriculum documents is database • Heikki Topi drew a comparison between the topics related to databases in the ACM/IEEE-CS CC2001 and the ACM/AIS IS recommendation • Size of figure represents degree of emphasis

11. CS IM14 IS 1.6.8 Digital Libraries CS IM10 Distributed Databases… Data Mining CS IM6 Relational Database Design CS IM9 IS 1.6.3 Physical Database Design Normalization IS 1.6.7 Intelligent QueryProcessors… IS 1.6.11 Data and DB Administration CS IM11 Information Storage and Retrieval IS 1.6.13 Information Retrieval CS IM13 CS IM12 Multimedia Informationand Systems Hypertext and Hypermedia CS IM8 Distributed Databases CS IM3 IS 1.6.2 CS IM7 Data Modeling CS IM4 IS 3.3.2 Relational Databases Transaction Processing IS 1.6.6 IS 1.6.4 Data Models Data Modeling Application Interface Integrity CS IM5 IS 1.6.12 Database Query Languages IS 1.6.5 Data Dictionary… Data DefinitionLanguages CS IM2 IS 1.6.1 IS 1.6.9 DBMS: features, functions, architecture DBMS Products IS 1.6.10 Database Systems Database machines and servers

12. And that does not include all levels of detail … Goal: an interactive structure for representation and exploration of the unified body of knowledge of all of the computing and information related disciplines

13. To what end? • Support program development • See where each proposed program fits in the constellation of computing related activities • Assist with program validation • Match proposed objectives and outcomes to required topic areas and levels of learning • Support updates of curriculum recommendations • Extensible and renewable, the ontology will keep up to date with emerging subjects and their roles • Document relationships with related disciplines • Keep in touch with advances that influence computing and connect with areas that touch computing • Development of interdisciplinary programs • Let others see what the computing disciplines offer

14. Desired outcomes • Keep computing related disciplines as a single voice to maintain strength • Maintain a current classification scheme for computing and information related work • Address the challenges of updated curriculum recommendations • Support curriculum development for creative new types of programs of study • Ease the path toward accreditation for non-standard programs of study

15. Not just for curriculum • This is not just for curriculum development and comparison • Research work is tagged with appropriate topic areas to facilitate groupings and support searching • If well done, this project could lead to more effective categorization of related research

16. What are we doing? • Careful review of existing classification systems • Perspectives of various sub cultures within computing • Computer engineering, computer science, information systems, information technology, software engineering • Consider both educational and research classification requirements

17. What is the difference • between a taxonomy and an ontology? • An ontology gives more than a list of terms with subtopic relationships • An ontology also encodes relationships that allow inferences to be drawn, new knowledge created from what is encoded.

18. Business Continuity Business IT Interface Business Process Modelling and Management Communication Compliance and Legislation Content Management Finance Future of Computing Government Issues Internet Offshoring Open Source Programming and Software Professional Issues Project Management Security Social Inclusion Spam Standards Storage IT subject areas (BCS)

19. ACM CCS Top Level • General Literature • Hardware • Computer Systems Organization • Software • Data • Theory of Computation • Mathematics of Computing • Information Systems • Computing Methodologies • Computer Applications • Computing Milieux

20. ACS Core Body of Knowledge • Computer Organisation and Architecture • Conceptual Modeling • Database Management • Data Communications and Networks • Discrete Mathematics • Ethics/Social Implications/ Professional Practice • Interpersonal Communications • Program Design and Implementation • Project management and quality assurance • Security • Software Engineering and Methodologies • Systems analysis and design • Systems software

21. German Accreditation • Automata and formal languages • Algorithms and data structures • Databases • Operations systems • Communication systems (particularly networks) • Computer architecture • Programming engineering • Software engineering (particularly modeling) and project management • Projects with high software engineering content

22. And more • Of course, there are others. • The point is that these are all related, but they express similar ideas differently and have some substantive differences

23. Simplification • Can we get a less complicated list of topics that defines what the computing and information disciplines are about?

24. Basic elements • What are we about? • Hardware • Software • Information • Human related aspects • “Human Factors” is a nice term, but has too much meaning attached to it. • But that is not enough to describe all that concerns the computing and information related disciplines

25. Topics of interest include all the core elements, and every possible combination of them HW Hu SW HW HW Hu HW SW HW Hu Inf HW SW Inf SW Hu Hu Inf SW Inf Inf Hu Inf SW But, that does not tell the whole story either.

26. For much of what we do, a system view of the parts is essential HW Hu SW HW HW Hu HW SW HW Hu Inf HW SW Inf SW Hu Hu Inf SW Inf Inf Hu Inf SW System But, not enough

27. The Application Context is often an inseparable part of the field. HW Hu SW HW HW Hu HW SW HW Hu Inf HW SW Inf SW Hu Hu Inf SW Inf Inf Hu Inf SW System But, there is more Application Context

28. Administer & Support Design, Combine, Build, Test HW Hu SW HW HW Hu HW SW HW Hu Inf HW SW Inf SW Hu Hu Inf SW Inf Inf Hu Inf SW System Application Context Social context

29. Administer & Support Design, Combine, Build, Test HW Hu SW HW HW Hu HW SW HW Hu Inf HW SW Inf SW Hu Hu Inf SW Inf Inf Hu Inf SW System Application Context Social context

30. The challenge • A multidimensional problem • Basic elements • Views • Applications of views • Unrestricted combinations

31. Topics and Outcomes • In the Education domain • A comprehensive set of topics does not begin to solve all the problems we listed. • The topic space is a tool to be incorporated into applications that address these issues. • It does not stand on its own.

32. Proficiency and Competency • Curriculum development moving toward an outcomes orientation. • Don’t tell me what topics you studied, tell me what you can do. • Clearly, an organized study of subject areas contributes to gaining proficiency in some area.

33. Learning outcomes Configure new wireless router

34. Beyond the body of knowledge • IFIP group identified seven aspects of curriculum development: • Body of Knowledge • Foundational Material • Application Context • Social Context • Breadth and Depth • Thematic Coherence • Outcomes The Ontology is a representation of the BoK Rules in the Ontology identify BoK elements with other aspects of this overall scheme L Cassel, G. Davies and D. Kumar. The shape of an evolving discipline in Informatics Curricula and Teaching Methods, L N Cassel and R Reis, Eds. Kluwer Academic Publishers. pp131-138

35. The body of knowledge for a given curriculum or program of study is drawn from the entirety of the related disciplines. • The other aspects must be combined with the BoK elements to form a viable program.

36. Imagine possibilities • Map a program of study onto the entirety of the disciplines. • Explore for the underrepresented areas. • Demonstrate the coverage of a planned curriculum. • Illustrate the distinctions and overlaps between existing and proposed specialties and related disciplines.

37. Other uses • Research classification • Imagine possibilities: • Researcher submitting a work • Researcher with a new idea, looking for related work and gaps in the knowledge base • Graduate student looking for a good topic • … etc.

38. Classification not a static labeling, but an insertion into a dynamic environment. • Search not just for a particular paper or author, but for what is around a topic area. • Exploration for areas that are richly filled and others that are sparse.

39. Current Status • Good list of topics • Never complete, dynamic • Organized as a taxonomy • Working on establishing the rules and relationships that change a taxonomy into an ontology • ACM has recently updated CCS • Reviewing to be sure all is included in our lists

40. Example efforts An Architectural Model

41. An example

44. Remember this? We need to make a very complex underlying structure produce just what is needed for a given purpose. Learning outcomes Configure new wireless router

45. What’s next • Enlisting the help of others • In subject areas • In educational needs • To establish the right linkages, and the right level of detail to include. • Encode the information about the topics and the relationships into a standard OWL file so that applications can be built against it • Develop prototype applications to demonstrate the potential so that others will develop more.

46. Discussion topics? • Feelings about a common reference point • Note: not a common idea of what constitutes a good or appropriate program! • Priorities • What types of information is most urgently needed? • How can this project help?

47. Contributors • This work is part of a project funded by a grant from the National Science Foundation, the ACM Education Board, and the IEEE-CS. • The Team: Boots Cassel (chair), Jim Cross, Gordon Davies, Reza Kamali, Eydie Lawson, Rich LeBlanc, Andrew McGettrick, Russ Shackelford, Bob Sloan, Heikki Topi, • Also contributing: Fred Mulder, and Anneke Hacquebard, Maarten van Veen • Growing list of interested parties

48. Follow our progress: what.csc.villanova.edu/twiki/bin/view/Main/OntologyProject