SOCoP 2013 Workshop:

Vision and StrategyGary Berg-Cross

SOCoP Executive SecretaryNov. 18-19 2012

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 Sessions1. 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/or2. 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

UnderstandingConceptualization

(C)(part of) the world

In some Conceptual Domain space

UML OWL

3. To express part of C we use a Language L

IntendedModelFitting

C

Adapted liberally from Nicola Guarino’s 1998Formal 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.

http://www.geoinfo.info/geoinfo2012/programa.php

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 RelationsSmall DUL Portion <owl:Class rdf:ID="SocialObjectAttribute"> <rdfs:label xml:lang="en">Social attribute</rdfs:label> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty> <owl:ObjectProperty rdf:ID="isRegionFor"/> </owl:onProperty> <owl:allValuesFrom> <owl:Class rdf:ID="SocialObject"/> </owl:allValuesFrom> </owl:Restriction> </rdfs:subClassOf> <rdfs:label xml:lang="it">Caratteristica sociale</rdfs:label> <rdfs:subClassOf> <owl:Class rdf:ID="Region"/> </rdfs:subClassOf> <rdfs:comment>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.</rdfs:comment>

</owl:Class> <owl:Class rdf:ID="WorkflowExecution">…

ODP

Abstract From

Use for

NewOntology Design

“Unfriendly logical structures, some large, hardly comprehensibleOntologies” (Aldo Gangemi)