Posts Tagged ‘community semantics management’

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 Many others are rather outdated prototypes, not “usable and reusable”, and unworthily categorised ontologies as an agreement on the schema vocabulary is non-existing.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.


Keynote at ESAS/COMPSAC2008 (Turku, Finland): Ontological Foundations for Evolving Agent Communities

August 1, 2008

De Leenheer, P. (2008) Keynote: Ontological Foundations for Evolving Agent Communities. In Proc of 32nd Annual IEEE International Computer Software and Applications Conference (COMPSAC 2008), IEEE Press, pp. 523-528

In July, I was invited for a talk at the 32nd Annual IEEE International Computer Software and Applications Conference in the track of Engineering Semantic Agent Systems.

30072008164Research in ontology management has reached a certain level of maturity, however, there is still little  understanding of, and technological support for, the methodological  and evolutionary aspects of ontologies as resources. Yet these are  crucial in distributed and collaborative worlds such as the Semantic  Web, where ontologies and their communities of use naturally and  mutually co-evolve. Through a deep understanding of the real-time,  community-driven, evolution of so-called ontologies, a semantic  agent system can be made operationally relevant and sustainable over  long periods of time. Such a paradigm shift in knowledge-intensive and  community-driven systems  would affect knowledge  sharing and communication across diverse communities in business,  industry, and society. This talk gives an overview of the practical and theoretical challenges and limitations, and based on that introduce an ontological and methodological foundation for community evolution processes.

Furthermore, we show how these theoretical foundations feed the development of business semantics management in Collibra.

Mind the Gap: Transcending the Tunnel Vision on Ontology Engineering.

November 17, 2007

De Leenheer, P. and Christiaens, S. (2007) Mind the Gap: Transcending the Tunnel Vision on Ontology Engineering. In Proc. of the 2nd Int’l Conf. on the Pragmatic Web 2007 (Tilburg, NL). ACM Press

The key objective of communal knowledge sharing at the scale of the World Wide Web is the ability to collaborate and integrate within and between communities. Ontologies, being formal, computer-based specifications of shared conceptualisations of the worlds under discussion, are instrumental in this process by providing shared semantic resources. To this end, the pragmatic aspects of the exchange of knowledge and information are crucial. Pragmatics represent the intentions, motivations and methodologies of the persons involved and need to become formalised and unambiguous for effective exchange to occur. On the one hand, this is something that humans manage fluently in their daily face-to-face social discourses. On the other hand, as contemporary knowledge engineering methods consider only the non-human system parts, they usually focus on mere syntactic aspects of concept modelling. The elicitation (semantics) and application (pragmatics) context are often weak or even ignored. This paper aims to bridge this gap between “reality” and its modelling concepts by (i) transcending knowledge engineering methods to a semiotics view on contextualised communal knowledge engineering and sharing; and (ii) by presenting the DOGMA ontology framework and how it provides extension points to this semiotics engineering.

[…] In order to illustrate the gap between knowledge sharing among people and information exchange at the technical system level we mentioned between the social/human knowledge-sharing system and its technical “mirror”, we adopt Nonaka’s well-known four modes of knowledge conversion [18] (see figure).

Through socialisation, people naturally utter and share experience and expertise in face-to-face discourses, and thereby create tacit knowledge such as mental models of ontological concepts and new technical skills. The current application context is about the concept Deliver.

Through externalisation, this tacit knowledge is partly articulated (publicly or privately) into explicit formal knowledge artefacts, taking the shape of e.g., a concept type, a contributed taxonomy, an interface, a workflow definition, etc. This is illustrated by the curved arrows that take a selection from the mental models that is relevant to explicate the concept Deliver in this application context. Note that although externalisation is an incremental process using language of variable expressivity (as we will explain below), there will inevitably remain an important part of tacit knowledge in the utterer’s mental model on which the correct interpretation of the articulated part is dependent [20,21]. Externalisation is done by domain experts, as they have the tacit knowledge about the domain and can sufficiently assess the real impact of the conceptualisations and derived collaborative services on their organization.

Once they are published, combination involves semantic analysis and integration (for an excellent survey, see [15]) of published contextualised knowledge artefacts in order to adapt to new collaborative requirements. This process might be further constrained by community-shared models such as running application tools that commit to certain published consensus, by pre-existing organisational sub-ontologies, and by inflexible data schemas interfacing to legacy data. Furthermore, participating stakeholders usually have strong individual interests, inherent business rules, and entrenched work practices that influence decisions in meaning negotiation rounds. These may be tacit, or externalised in workflows that are strongly interdependent, hence further complicate the conceptual combination. Sometimes it is not necessary (or even possible) to reach for context-independent ontological knowledge, as most ontologies used in practice assume a certain context and perspective of some community [23]. Wenger [26] supported this by stating “Peace, happiness, and harmony are therefore not necessary properties of a community of practice”. Hence pragmatically, combination processes need to support human experts to focus on these “community-grounded” processes of realising the appropriate amount of consensus on relevant conceptual definitions through effective meaning negotiation in an efficient manner [7].
Internalisation concerns the appropriate operationalisation and embodiment of explicit knowledge consensus in the current communication actions. For example, for ontological knowledge, the most widely used recommendations on the Semantic Web are XML, RDF(S) and OWL.

The four modes of knowledge conversion engender an upward knowledge spiral, where individual knowledge opinions become commonly accepted, through an iterative interplay between externalisation and internalisation. This interplay illustrates how knowledge artefacts co-evolve with their communities of use. In socialisation, knowledge is communicated as abstract entities, and humans can easily grasp the context of interpretation. However, when applying formal knowledge engineering methods for the other knowledge conversion modes, we have to emphasize the semiotic dimensions, in order to bridge the gap between socialisation processes in the social system on the one hand, and the other conversion processes (externalisation, internalisation, and combination) in the technical system on the other hand.

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.