732 research outputs found
XML for Domain Viewpoints
Within research institutions like CERN (European Organization for Nuclear
Research) there are often disparate databases (different in format, type and
structure) that users need to access in a domain-specific manner. Users may
want to access a simple unit of information without having to understand detail
of the underlying schema or they may want to access the same information from
several different sources. It is neither desirable nor feasible to require
users to have knowledge of these schemas. Instead it would be advantageous if a
user could query these sources using his or her own domain models and
abstractions of the data. This paper describes the basis of an XML (eXtended
Markup Language) framework that provides this functionality and is currently
being developed at CERN. The goal of the first prototype was to explore the
possibilities of XML for data integration and model management. It shows how
XML can be used to integrate data sources. The framework is not only applicable
to CERN data sources but other environments too.Comment: 9 pages, 6 figures, conference report from SCI'2001 Multiconference
on Systemics & Informatics, Florid
PAV ontology: provenance, authoring and versioning
Provenance is a critical ingredient for establishing trust of published
scientific content. This is true whether we are considering a data set, a
computational workflow, a peer-reviewed publication or a simple scientific
claim with supportive evidence. Existing vocabularies such as DC Terms and the
W3C PROV-O are domain-independent and general-purpose and they allow and
encourage for extensions to cover more specific needs. We identify the specific
need for identifying or distinguishing between the various roles assumed by
agents manipulating digital artifacts, such as author, contributor and curator.
We present the Provenance, Authoring and Versioning ontology (PAV): a
lightweight ontology for capturing just enough descriptions essential for
tracking the provenance, authoring and versioning of web resources. We argue
that such descriptions are essential for digital scientific content. PAV
distinguishes between contributors, authors and curators of content and
creators of representations in addition to the provenance of originating
resources that have been accessed, transformed and consumed. We explore five
projects (and communities) that have adopted PAV illustrating their usage
through concrete examples. Moreover, we present mappings that show how PAV
extends the PROV-O ontology to support broader interoperability.
The authors strived to keep PAV lightweight and compact by including only
those terms that have demonstrated to be pragmatically useful in existing
applications, and by recommending terms from existing ontologies when
plausible.
We analyze and compare PAV with related approaches, namely Provenance
Vocabulary, DC Terms and BIBFRAME. We identify similarities and analyze their
differences with PAV, outlining strengths and weaknesses of our proposed model.
We specify SKOS mappings that align PAV with DC Terms.Comment: 22 pages (incl 5 tables and 19 figures). Submitted to Journal of
Biomedical Semantics 2013-04-26 (#1858276535979415). Revised article
submitted 2013-08-30. Second revised article submitted 2013-10-06. Accepted
2013-10-07. Author proofs sent 2013-10-09 and 2013-10-16. Published
2013-11-22. Final version 2013-12-06.
http://www.jbiomedsem.com/content/4/1/3
Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain
Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains. Many ontology-related terms with precise meanings in one of these domains have different meanings in others. Our purpose here is to initiate a path towards disambiguation of such terms. We draw primarily on the literature of biomedical informatics, not least because the problems caused by unclear or ambiguous use of terms have been there most thoroughly addressed. We advance a proposal resting on a distinction of three levels too often run together in biomedical ontology research: 1. the level of reality; 2. the level of cognitive representations of this reality; 3. the level of textual and graphical artifacts. We propose a reference terminology for ontology research and development that is designed to serve as common hub into which the several competing disciplinary terminologies can be mapped. We then justify our terminological choices through a critical treatment of the ‘concept orientation’ in biomedical terminology research
Ontology as Product-Service System: Lessons Learned from GO, BFO and DOLCE
This paper defends a view of the Gene Ontology (GO) and of Basic Formal Ontology (BFO) as examples of what the manufacturing industry calls product-service systems. This means that they are products (the ontologies) bundled with a range of ontology services such as updates, training, help desk, and permanent identifiers. The paper argues that GO and BFO are contrasted in this respect with DOLCE, which approximates more closely to a scientific theory or a scientific publication. The paper provides a detailed overview of ontology services and concludes with a discussion of some implications of the product-service system approach for the understanding of the nature of applied ontology. Ontology developer communities are compared in this respect with developers of scientific theories and of standards (such as W3C). For each of these we can ask: what kinds of products do they develop and what kinds of services do they provide for the users of these products
Generic adaptation framework for unifying adaptive web-based systems
The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the most general architectures of the present and future, including conventional AHS, and different types of personalization-enabling systems and applications such as recommender systems (RS) personalized web search, semantic web enabled applications used in personalized information delivery, adaptive e-Learning applications and many more. At the same time GAF is trying to bring together two (seemingly not intersecting) views on the adaptation: a classical pre-authored type, with conventional domain and overlay user models and data-driven adaptation which includes a set of data mining, machine learning and information retrieval tools. To bring these research fields together we conducted a number GAF compliance studies including RS, AHS, and other applications combining adaptation, recommendation and search. We also performed a number of real systems’ case-studies to prove the point and perform a detailed analysis and evaluation of the framework. Secondly it introduces a number of new ideas in the field of AH, such as the Generic Adaptation Process (GAP) which aligns with a layered (data-oriented) architecture and serves as a reference adaptation process. This also helps to understand the compliance features mentioned earlier. Besides that GAF deals with important and novel aspects of adaptation enabling and leveraging technologies such as provenance and versioning. The existence of such a reference basis should stimulate AHS research and enable researchers to demonstrate ideas for new adaptation methods much more quickly than if they had to start from scratch. GAF will thus help bootstrap any adaptive web-based system research, design, analysis and evaluation
Evaluating FAIR Digital Object and Linked Data as distributed object systems
FAIR Digital Object (FDO) is an emerging concept that is highlighted by
European Open Science Cloud (EOSC) as a potential candidate for building a
ecosystem of machine-actionable research outputs. In this work we
systematically evaluate FDO and its implementations as a global distributed
object system, by using five different conceptual frameworks that cover
interoperability, middleware, FAIR principles, EOSC requirements and FDO
guidelines themself.
We compare the FDO approach with established Linked Data practices and the
existing Web architecture, and provide a brief history of the Semantic Web
while discussing why these technologies may have been difficult to adopt for
FDO purposes. We conclude with recommendations for both Linked Data and FDO
communities to further their adaptation and alignment.Comment: 40 pages, submitted to PeerJ C
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