SOCoP 2013 Workshop: Vision and Strategy Gary Berg-Cross SOCoP Executive Secretary Nov NSF Stafford II facility Wilson Blvd, Ballston VA

2 VoCamp-Style Workshop VoCamp Style is informal –an unconference But the Workshop has Ingredients for success 1. Goals 2. Workgroup Teams 3. Employs a Phased Structure for Work Sessions 1. Ontological Engineering 2. From Conceptualizations to Formalizations 4. Cautions and Tradeoffs 5. Lighter Ontologies and Ontology Patterns While educational we are not here to teach a new discipline, but to employ multiple disciplines as a team.

3 Goals- Build on Past workshops, Interests, Experience 1. We seek clarified agreement & reduced ambiguities/conflicts on geospatial & related phenomena (e.g. earth sciences) that can be formally represented in: 1. Constrained, engineered models to support understanding, reasoning & data interoperability and/or 2. Creation of general patterns that provide a common framework to generate ontologies that are consistent and can support interoperability. 2. We like data-grounded work since: 1. Much of the utility of geospatial ontologies will likely come from their ability to relate geospatial data to other kinds of information.

4 Workgroups/Breakouts Include Multiple Roles: “Group Work on Semantic Models of Interest” Semantic Engineering is a Social Process Ontologist Domain/Data Expert Facilitator Note taker

5 Logic of Work Sessions Start Group organization & Introductions, goals and process After lunch Group Work on Concepts, Vocabulary & Model(s) After break Group Work on Draft Models At end of day Group Reports on status At end of day Report back to whole and wrap up 2nd day draft final model & initial formalizations After break Work Groups polish, formalize models After lunch firm up products and test against data After break Prepare Report Start Here Day One Intro, Topics, Methods..

6 Ontological Engineering – Concepts to Formalization 1 World Situations Interaction..That is a type of Stream segment Understanding Conceptualization (C) (part of) the world In some Conceptual Domain space UML OWL 3. To express part of C we use a Language L Intended Model Fitting C Adapted liberally from Nicola Guarino’s 1998 Formal Ontology in Information Systems 2. Systematic organization & framing Model 1.Problems, Component and Relation Identification & Clarification 3.Formalization

7 Caution(s) & Tradeoffs - But these, of course, make the work interesting….. No single (general or domain) subsumption taxonomy or ontology could satisfy all needs. so we have many alternative ones. We believe that can make quality, useful ones for one or more purposes. We need “intended models” of focus. Caution - if we make commitments that make strong claims that are greater our understanding and focus we may be making a mistake(s). Consider tradeoffs between generality and precision. Paraphrasing Tom Bittner in Vagueness and the tradeoff between the classification and delineation of geographic regions - an ontological analysis many geometric representations, rely on relatively precise boundaries, this conflicts with sophisticated (practical?) classification systems for scientific and integration purposes. 

8 ODPs (aka microtheories) small, well engineered, modular starter set of Models Our Problem It is hard to reuse only the “useful pieces" of a comprehensive (foundational) ontology, and the cost of reuse may be higher than developing a scoped ontology for particular purpose from scratch “For solving semantic problems, it may be more productive to agree on minimal requirements imposed on.. Notion(s) Werner Kuhn (Semantic Engineering, 2009) Solution Approach Use small, well engineered coherent, minimally constrained schemas as modular starter set ontologies (ODPs) with explicit documentation of design rationales, best reengineering practices to facilitate reuse, ODPs serve as an initial constraining network of “concepts” with vocabulary which people may build on/from for various purposes.

9 Ontology-ODP Relations Small DUL Portion Social attribute Caratteristica sociale Any Region in a dimensional space that is used to represent some characteristic of a SocialObject, e.g. judgment values, social scalars, statistical attributes over a collection of entities, etc. … ODP Abstract From Use for New Ontology Design “Unfriendly logical structures, some large, hardly comprehensible Ontologies” (Aldo Gangemi)