Posts Tagged ‘dogma-mess’

Principles of ICT Democracy: can communities themselves build their ontologies ?

March 4, 2009

The second-generation Web (2.0) is a complex socio-technical system of unforeseen growth and dynamics. On-line communities emerge and interact all around a usually self-organising manner supported by interactive applications, including bookmarking, tagging, blogging, and wikis, being developed and shared at little or no cost.  The emerging range of Semantic Web and other open technologies promises an increase in scale and maturity of knowledge sharing, achieved through collaboration and integration within and between diverse communities.

Considering the current pace of social and technological development, it seems that the transformation of the Web from a network of separately siloed applications and content repositories to a more seamless and semantically interoperable ecosystem is at hand, opening a wide range of scientific challenges and opportunities. However, while simple, the idea of the Semantic Web remains largely unrealised.

Semantic interoperability is the ability of two or more information systems or their (computerised) components to communicate data and to interpret the information in the data that has been communicated both in a meaningful manner, that is by means of an ontology that is shared by the involved information systems.

The ontologies that will furnish the Semantic Web are lacking, and those few that have been published are usually not based on consensus, and hence unreliable and not reusable beyond individual purposes. Of those domain vocabularies that are published on the Web, only some of them are actively maintained and thus reflect the current domain. Many others are rather outdated prototypes, not “usable and reusable”, and unworthily categorised ontologies as an agreement on the schema vocabulary is non-existing. Current techniques that claim to create semantic interoperability are unsatisfactory, both theoretically and as far as the quality of the results is concerned. In current ontology engineering practice, the underlying methodological pinciples are mostly ignored.

In current ontology engineering practices, the underlying methodological principles are mostly ignored. Furthermore, they systemically disregard the subtle gap that looms between knowledge sharing among people at the community/social level on the one hand; and information exchange between computer systems at the operational/technical level (see figure below).

The gap between knowledge sharing between human beings as an act of socialisation and information exchange between computer systems.

The gap between knowledge sharing between human beings as an act of socialisation and information exchange between computer systems.

Architecting community-driven internet systems will require a paradigm shift that goes beyond mere technological fits. In order to bridge the gap between the social and technical part of the community, one must put into practice the necessary activities to identify common needs from socialisation activities and bring the stakeholders together to find and ontological agreement to support these needs.

Community-based ontology evolution establishes the co-evolution of (A)  social interactions enabled by the community’s design; (B) the information systems that support them; and (C) the semantic patterns to fulfil semantic interoperability between these systems.

In order to enact this co-evolution we start from the following seven principles that every approach should keep in mind:

  1. ICT Democracy An ontology should be defined by its community, and not by a single developer.
  2. Autonomy Semantic interoperability requirements emerge autonomously from community evolution processes.
  3. Co-evolution Ontology evolution processes are driven by the changing semantic interoperability requirements.
  4. Perspective Rendering Ontology evolution processes must reflect the various stakeholders’ perspectives.
  5. Perspective Unification In building the common ontology, relevant parts of the various stakeholder perspectives serve as input for the unified perspective.
  6. Validation The explicit rendering of stakeholders perspectives allows us to capture the ontology evolution process completely, and validate the ontology against these perspectives respectively.
  7. Satisfaction Ultimately, co-evolving communities with their ontology will increase overall stakeholder satisfaction.

Community/business semantics management is our approach to enact community-based ontology evolution.

Business Semantics Management: a Case Study for Competency-centric HRM

January 16, 2009

In this article we introduce a novel approach and tool for fact-oriented business semantics management that is inspired by agile design methods. We demonstrate and validate it in a realistic case study that was carried out within the European Codrive project. Codrive’s vision was to contribute to more meaningful competency-centric human resource management. Key challenges are the uniform publication of unambiguous competency information and “time-to-competency” agility. To this end, we developed a shared and formal knowledge representation of competency domains. Stakeholders include educational institutes, public employment organisations, and industry partners from different European countries. The resulting Vocational Competency Ontology wanted to provide a candidate best practice for engineering a community-shared and reusable semantic pattern base that can be applied by all stakeholders to semantically reconcile their contextualised competency models.businesssemanticsmanagement De Leenheer, P., Christiaens, S., and Meersman, R. (2009) Business Semantics Management: a Case Study for Competency-centric HRM. In Journal of Computers in Industry: Special Issue about Semantic Web Computing in Industry. Elsevier, forthcoming

DOGMA-MESS: A Tool for Fact-Oriented Collaborative Ontology Evolution

November 14, 2008

ontologyeditorontology

Ontologies being shared formal specifications of a domain, are an important lever for developing meaningful internet systems. However, the problem is not in what ontologies are, but how they become operationally relevant and sustainable over longer periods of time. Fact-oriented and layered approaches such as DOGMA have been successful in facilitating domain experts in representing and understanding semantically stable ontologies, while emphasising reusability and scalability. DOGMA-MESS, extending DOGMA, is a collaborative ontology evolution methodology that supports stakeholders in iteratively interpreting and modeling their common ontologies in their own terminology and context, and feeding back these results to the owning community. In this paper we extend DOGMA Studio with a set of collaborative ontology evolution support modules.

De Leenheer, P. and Debruyne C. (2008) DOGMA-MESS: A Tool for Fact-Oriented Collaborative Ontology Evolution. In Proc. of On the Move to Meaningful Internet Systems 2008: ORM (ORM 2008) (Monterrey, Mexico), LNCS 5333, Springer, pp. 797-806

Community-driven Evolution of Knowledge-intensive Systems

November 26, 2007

De Leenheer, P. and Meersman, R. (2007) Towards Community-driven Evolution of Knowledge-intensive Systems. In Proc. of the 6th Int’l Conf. on Ontologies, DataBases, and Applications of Semantics (ODBASE 2007) (Vilamoura, Portugal), LNCS, Springer

Co-evolution in a knowledge-intensive community

Co-evolution in a knowledge-intensive community

This article wants to address the need for a research effort and framework that studies and embraces the novel, difficult but crucial issues of adaptation of knowledge resources to their respective user communities, and \emph{vice versa}, as a fundamental property within knowledge-intensive internet systems. Through a deep understanding of real-time community-driven evolution of so-called ontologies, a knowledge-intensive system can be made operationally relevant and sustainable over longer periods of time. To bootstrap our framework, we adopt and extend the DOGMA ontology framework, and its community-grounded ontology engineering methodology DOGMA-MESS, with an ontology that models community concepts such as business rules, norms, policies, and goals as first-class citizens of the ontology evolution process. Doing so ontology evolution can be tailored to the needs of a particular community. Finally, we illustrate with an example from an actual real-world problem setting, viz. interorganisational exchange of HR-related knowledge.

Using Graph transformation for Collaborative Ontology Evolution

October 16, 2007

De Leenheer, P. and Mens, T. (2007) Using Graph transformation for Collaborative Ontology Evolution. Proc. of the Third International Symposium on Applications of Graph Transformation with Industrial Relevance (AGTIVE 2008) (Kassel, Germany), LNCS 5088, Springer.changedifftosibling

In collaborative ontology engineering, contexts are key to manage the complexity of different dependency types between ontological artefacts. Instead of being frustrated by out-of-control evolution processes, proper context dependency management will allow human experts to focus on the meaning interpretation and negotiation processes. This requires support for the detection and resolution of meaning ambiguities and conflicts. In this article, we explore to which extent the theory of graph transformation can be used to support this activity. More specifically, we propose the use of critical pair analysis as a formal means to analyse conflicts between ontologies that are evolving in parallel. We illustrate this with an example from a realistic case study.

Context Dependency Management in Ontology Engineering: a Formal Approach

June 12, 2007

jods_viii_deleenheer_fig1A viable ontology engineering methodology requires supporting domain experts in gradually building and managing increasingly complex versions of ontological elements and their converging and diverging interrelationships. Contexts are necessary to formalise and reason about such a dynamic wealth of knowledge. However, context dependencies introduce many complexities. In this article, we introduce a formal framework for supporting context dependency management processes, based on the DOGMA framework and methodology for scalable ontology engineering. Key notions are a set of context dependency operators, which can be combined to manage complex context dependencies like articulation, application, specialisation,
and revision dependencies. In turn, these dependencies can be used in context-driven ontology engineering processes tailored to the specific requirements of collaborative communities. This is illustrated by a real-world case of interorganisational competency ontology engineering.

De Leenheer, P., de Moor, A., and Meersman, R. (2007) Context Dependency Management in Ontology Engineering: a Formal Approach. Journal on Data Semantics VIII, LNCS 4380, Springer-Verlag, pp. 26-56.

DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering

June 17, 2006

de Moor, A., De Leenheer, P., and Meersman, R. (2006) DOGMA-MESS: A Meaning Evolution Support System for Interorganizational Ontology Engineering . In Proc. of the 14th Int’l Conference on Conceptual Structures (ICCS 2006) (Aalborg, Denmark), LNAI 4068, Springer, pp. 189-203.

In this paper, we explore the process of interorganizational ontology engineering. Scalable ontology engineering is hard to do in interorganizational settings where there are many pre-existing organizational ontologies and rapidly changing collaborative requirements. A complex socio-technical process of ontology alignment and meaning negotiation is therefore required.   In particular, we are interested in how to increase the efficiency and ioe2relevance of this process using context dependencies between ontological elements. We describe the DOGMA-MESS methodology and system for scalable, community-grounded ontology engineering. We illustrate this methodology  with examples taken from a case of interorganizational competency ontology evolution in the vocational training domain.

Disambiguation of Natural-language Terms in Business Semantics Engineering

July 10, 2005

De Leenheer, P. and de Moor, A. (2005) Context-driven Disambiguation in Ontology Elicitation. In Shvaiko P. & Euzenat J.,(eds.), Context and Ontologies: Theory, Practice and Applications, AAAI Technical Report WS-05-01 (Pittsburgh, Pennsylvania), AAAI Press, pp. 17–24.

dogma_method

Illustration of the two levels in DOGMA ontology: on the left -- the lexical level, lexons are elicited from various contexts. On the right, there is the conceptual level consisting of a concept definition server. The meaning ladder in between illustrates the articulation of lexical terms into concept definitions.

Ontologies represent rich semantics in a lexical way. Lexical labels are used to identify concepts and relationships, though there is no bijective mapping between them. Phenomenons such as synonyms and homonyms exemplify this, and can result in frustrating misunderstanding and ambiguity. In the elicitation and application of ontologies, the meaning of the ontological knowledge is dependent on the context. We consider the role of context in ontology elicitation by introducing context in a concept definition server for ontology representation. We also adopt other features of context found in literature, such as packaging of knowledge, aligning elements of different contexts, and reasoning about contexts. Finally, we illustrate context-driven ontology elicitation with a real world case study.

This paper was further extended in Journal of Data Semantics. See my related blog in this. In our business semantics management approach, disambiguation forms an important but difficult exercise during the consolidation activities.


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