741 research outputs found
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Global integration of public sector information
This paper deals with technological methods for consolidating assets lists of available public sector information (PSI) for re-use. In this direction, the effort is to review the state of the art in delivering access to PSI throughout the world and to prioritize the necessary engagements for joining available PSI catalogues. We propose an architectural framework grounded on Semantic Web technologies to deliver a global platform for federated searching. A speculative survey of available PSI portals is presented, and the initial implementation, results, and analysis of the proposed architecture are covered in detail
Observing observatories: web observatories should use linked data
Web Observatories are a major international scientific collaboration concerned with data sources of a heterogeneous nature, and often quite large. Of course, they are not the first such collaboration; the Web itself was born as a response to a similar scientific endeavor. It is therefore appropriate to look at other col-laborative activities, and try to learn and use the lessons they have learnt.We argue that Web Observatories should build in interoperability using current best practices right from the start. We also argue that Linked Data is a best practice, and can provide the basis for a research environment that will deliver the vision of a large group of cooperating Observatories, sharing data and re-search results to the benefit of all. In addition, we argue that the activity should not start with a major standardization process, but should grow around appro-priate standards as required
Towards Ontology-Based Requirements Engineering for IoT-Supported Well-Being, Aging and Health
Ontologies serve as a one of the formal means to represent and model
knowledge in computer science, electrical engineering, system engineering and
other related disciplines. Ontologies within requirements engineering may be
used for formal representation of system requirements. In the Internet of
Things, ontologies may be used to represent sensor knowledge and describe
acquired data semantics. Designing an ontology comprehensive enough with an
appropriate level of knowledge expressiveness, serving multiple purposes, from
system requirements specifications to modeling knowledge based on data from IoT
sensors, is one of the great challenges. This paper proposes an approach
towards ontology-based requirements engineering for well-being, aging and
health supported by the Internet of Things. Such an ontology design does not
aim at creating a new ontology, but extending the appropriate one already
existing, SAREF4EHAW, in order align with the well-being, aging and health
concepts and structure the knowledge within the domain. Other contributions
include a conceptual formulation for Well-Being, Aging and Health and a related
taxonomy, as well as a concept of One Well-Being, Aging and Health. New
attributes and relations have been proposed for the new ontology extension,
along with the updated list of use cases and particular ontological
requirements not covered by the original ontology. Future work envisions full
specification of the new ontology extension, as well as structuring system
requirements and sensor measurement parameters to follow description logic.Comment: 10 pages, 2 figures, 2 table
Assigning Creative Commons Licenses to Research Metadata: Issues and Cases
This paper discusses the problem of lack of clear licensing and transparency
of usage terms and conditions for research metadata. Making research data
connected, discoverable and reusable are the key enablers of the new data
revolution in research. We discuss how the lack of transparency hinders
discovery of research data and make it disconnected from the publication and
other trusted research outcomes. In addition, we discuss the application of
Creative Commons licenses for research metadata, and provide some examples of
the applicability of this approach to internationally known data
infrastructures.Comment: 9 pages. Submitted to the 29th International Conference on Legal
Knowledge and Information Systems (JURIX 2016), Nice (France) 14-16 December
201
A Continuously Growing Dataset of Sentential Paraphrases
A major challenge in paraphrase research is the lack of parallel corpora. In
this paper, we present a new method to collect large-scale sentential
paraphrases from Twitter by linking tweets through shared URLs. The main
advantage of our method is its simplicity, as it gets rid of the classifier or
human in the loop needed to select data before annotation and subsequent
application of paraphrase identification algorithms in the previous work. We
present the largest human-labeled paraphrase corpus to date of 51,524 sentence
pairs and the first cross-domain benchmarking for automatic paraphrase
identification. In addition, we show that more than 30,000 new sentential
paraphrases can be easily and continuously captured every month at ~70%
precision, and demonstrate their utility for downstream NLP tasks through
phrasal paraphrase extraction. We make our code and data freely available.Comment: 11 pages, accepted to EMNLP 201
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