Stijn Christiaens

Metadata mechanisms: from ontology to folksonomy .. and back

In this paper we give a brief overview of different metadata mechanisms (like ontologies and folksonomies) and how they relate to each other We identify major strengths and weaknesses of these mechanisms We claim that these mechanisms can be classified from restricted (e.g., ontology) to free (e.g., free text tagging) In our view, these mechanisms should not be used in isolation, but rather as complementary solutions, in a continuous process wherein the strong points of one increase the semantic depth of the other We give an overview of early active research already going on in this direction and propose that methodologies to support this process be developed We demonstrate a possible approach, in which we mix tagging, taxonomy and ontology.

T-Lex: a role-based ontology engineering tool

In the DOGMA ontology engineering approach ontology construction starts from a (possibly very large) uninterpreted base of elementary fact types called lexons that are mined from linguistic descriptions (be it from existing schemas, a text corpus or formulated by domain experts) An ontological commitment to such ”lexon base” means selecting/reusing from it a meaningful set of facts that approximates well the intended conceptualization, followed by the addition of a set of constraints, or rules, to this subset The commitment process is inspired by the fact-based database modeling method NIAM/ORM2, which features a recently updated, extensive graphical support However, for encouraging lexon reuse by ontology engineers a more scalable way of visually browsing a large Lexon Base is important Existing techniques for similar semantic networks rather focus on graphical distance between concepts and not always consider the possibility that concepts might be (fact-) related to a large number of other concepts In this paper we introduce an alternative approach to browsing large fact-based diagrams in general, which we apply to lexon base browsing and selecting for building ontological commitments in particular We show that specific characteristics of DOGMA such as grouping by contexts and its ”double articulation principle”, viz explicit separation between lexons and an applications commitment to them can increase the scalability of this approach We illustrate with a real-world case study.

Business Semantics Management Supports Government Innovation Information Portal

The knowledge economy is one of the cornerstones of our society. Our economic prosperity and development is derived for a large part from technical knowledge. Knowledge unlocks innovation, which in turns spawns new products or services, thereby enabling further economic growth. Hence, an information system unlocking scientific technical knowledge is an important asset for government policy and strategic decisions by industry. In this paper it is explained how business semantics management and related tools are applied to realise the above mentioned endeavour.

Publishing open data and services for the Flemish research information space

The Flemish public administration aims to integrate and publish all research information on a portal. Information is currently stored according to the CERIF standard modeled in (E)ER and aimed at extensibility. Solutions exist to easily publish data from databases in RDF, but ontologies need to be constructed to render those meaningful. In order to publish their data, the public administration and other stakeholders first need to agree on a shared understanding of what exactly is captured and stored in that format. In this paper, we show how the use of the Business Semantics Management method and tool contributed in achieving that aim.

Competency model in a semantic context: meaningful competencies (position paper)

In this paper, we will propose our ideas for a semantically ready competency model The model will allow semantic enrichment on different levels, creating truly meaningful competencies The aim of this model is to provide a flexible approach for (re)use, matching, interpretation, exchange and storage for competencies Our competency model is based on the DOGMA ontology framework and the proposed IEEE standards RCD and SCRM We will focus on the model itself and how semantics can be applied to it as these elements form the basis for any kind of processing on them.

Ontology guided data integration for computational prioritization of disease genes

In this paper we present our progress on a framework for collection and presentation of biomedical information through ontology-based mediation The framework is built on top of a methodology for computational prioritization of candidate disease genes, called Endeavour Endeavour prioritizes genes based on their similarity with a set of training genes while using a wide variety of information sources However, collecting information from different sources is a difficult process and can lead to non-flexible solutions In this paper we describe an ontology-based mediation framework for efficient retrieval, integration, and visualization of the information sources Endeavour uses The described framework allows to (1) integrate the information sources on a conceptual level, (2) provide transparency to the user, (3) eliminate ambiguity and (4) increase efficiency in information display.

Challenges and Opportunities for More Meaningful and Sustainable Internet Systems

Despite its technological success story, the Internet is facing a rampant growth of isolated ontologies and a massive dump of unstructured legacy data. Therefore, architecting the next generation of the Internet will require a paradigm shift that goes beyond technological excellence. This is the main hypothesis we take and defend in this paper. Main drivers behind the dynamics of this future Web 3.0 are the massive and meaningful reconciliation of disparate data sources and service discovery, and the pervasiveness of these processes in daily life and work of on-line communities. Paving our way to more meaningful and sustainable internet systems, we devise a three-dimensional problem space from which we draw challenges and methodological opportunities. Next, based on this, we propose a DNS of Information. Finally, we substantiate our proposal with related research projects, practices, and initiatives that act as main catalysts or adopters.

SBVR-Driven Information Governance: A Case Study in the Flemish Public Administration

Databases persistently store data and provide standardised access to it for communities consisting of human as well as software agents. However, adequate information governance in such a bi-sortal setting requires more than that. Despite the rigorous formal structure that may have been imposed on a data set, if it cannot be disclosed to third parties, their value is practically zero. The ICT-outsourcing partnership between the Flemish Ministry of Education and Training (FMET) and EDS-Telindus, now HP, appreciated the subtle difference between data and information, and the need for more maturity regarding the governance of their vast (meta-)data landscape. This is shown by initiatives such as the development of a Data Warehouse and an Information Governance Organization.

Toward a Community Vision Driven Topical Ontology in Human Resource Management

Todays industries require ontology engineering to be more community vision driven and ontological resources have more dimensions. This paper shows our achieved goals in the EU Prolix project. Firstly, we analyze the user requirements, including tuning Business Process Modelling efforts into ontology engineering tasks. Secondly, we design a scalable and community driven architecture for ontology development. Then, feasible ontology models are created. The task of creating ontology models depends heavily on conceptual architecture of ontology based competence analysis. We illustrate with the requirement analysis from BT (British Telecom).

Methodological Approach to Determine Appropriately Annotated Resources in Narrow Folksonomies

Folksonomies are community managed vocabularies, and do not limit end users to employ a strict terminology in their annotating activities. Users are free to create and use whatever tag they like. Folksonomies have also been criticized to produce low quality meta data due to reduced quality control. In the case of narrow folksonomies where resources are evaluated by only one person there is no certainty that the resources are appropriately annotated. In this paper, we suggest a three-phase iterative approach to determine the properties, expressed in terms of tag ambiguity, of resources appropriately annotated in a narrow folksonomy to improve information retrieval. We also show brief results of the first steps of that approach in a case study involving a narrow folksonomy.