Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Economics and Engineering for Preserving Digital Content

Progress towards practical long-term preservation seems to be stalled. Preservationists cannot afford specially developed technology, but must exploit what is created for the marketplace. Economic and technical facts suggest that most preservation ork should be shifted from repository institutions to information producers and consumers. Prior publications describe solutions for all known conceptual challenges of preserving a single digital object, but do not deal with software development or scaling to large collections. Much of the document handling software needed is available. It has, however, not yet been selected, adapted, integrated, or deployed for digital preservation. The daily tools of both information producers and information consumers can be extended to embed preservation packaging without much burdening these users. We describe a practical strategy for detailed design and implementation. Document handling is intrinsically complicated because of human sensitivity to communication nuances. Our engineering section therefore starts by discussing how project managers can master the many pertinent details.

Software agents in support of human argument mapping

This paper reports progress in realizing human-agent argumentation, which we argue will be part of future Computer-Supported Collaborative Argumentation (CSCA) tools. With a particular interest in argument mapping, we present two investigations demonstrating how a particular agent-oriented language and architecture can augment CSCA: (i) the use of the IBIS formalism enabling Brahms agents to simulate argumentation, and (ii) the extension of the Compendium tool by integrating it with Brahms agents tasked with detecting related discourse elsewhere

A lexicon for biology and bioinformatics: the BOOTStrep experience

This paper describes the design, implementation and population of a lexical resource for biology and bioinformatics (the BioLexicon) developed within an ongoing European project. The aim of this project is text-based knowledge harvesting for support to information extraction and text mining in the biomedical domain. The BioLexicon is a large-scale lexical-terminological resource encoding different information types in one single integrated resource. In the design of the resource we follow the ISO/DIS 24613 ?Lexical Mark-up Framework? standard, which ensures reusability of the information encoded and easy exchange of both data and architecture. The design of the resource also takes into account the needs of our text mining partners who automatically extract syntactic and semantic information from texts and feed it to the lexicon. The present contribution first describes in detail the model of the BioLexicon along its three main layers: morphology, syntax and semantics; then, it briefly describes the database implementation of the model and the population strategy followed within the project, together with an example. The BioLexicon database in fact comes equipped with automatic uploading procedures based on a common exchange XML format, which guarantees that the lexicon can be properly populated with data coming from different sources

Data dictionary services in XNAT and the Human Connectome Project

The XNAT informatics platform is an open source data management tool used by biomedical imaging researchers around the world. An important feature of XNAT is its highly extensible architecture: users of XNAT can add new data types to the system to capture the imaging and phenotypic data generated in their studies. Until recently, XNAT has had limited capacity to broadcast the meaning of these data extensions to users, other XNAT installations, and other software.We have implemented a data dictionary service for XNAT, which is currently being used on ConnectomeDB, the Human Connectome Project (HCP) public data sharing website. The data dictionary service provides a framework to define key relationships between data elements and structures across the XNAT installation. This includes not just core data representing medical imaging data or subject or patient evaluations, but also taxonomical structures, security relationships, subject groups, and research protocols. The data dictionary allows users to define metadata for data structures and their properties, such as value types (e.g. textual, integers, floats) and valid value templates, ranges, or field lists. The service provides compatibility and integration with other research data management services by enabling easy migration of XNAT data to standards-based formats such as RDF, JSON, and XML. It also facilitates the conversion of XNAT’s native data schema into standard neuroimaging ontology structures and provenances.<br/