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- 21 creator david-corsar.
- 21 creator ian-piper.
- 21 creator laura-moss.
- 21 type InProceedings.
- 21 label "Data Quality Assessment Using Linked Data: A Case Study in the Medical Domain".
- 21 sameAs 21.
- 21 abstract "This paper describes an approach and framework based on semantic web and linked data technologies to assess medical data collected by patient monitoring equipment. Our approach has been successfully applied to patient data in the neuro-intensive care domain.".
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- 21 title "Data Quality Assessment Using Linked Data: A Case Study in the Medical Domain".
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- 22 creator gaoussou-camara.
- 22 creator moussa-lo.
- 22 creator rim-djedidi.
- 22 creator sylvie-despres.
- 22 type InProceedings.
- 22 label "A Study of an Infectious Disease Ontology: the Epidemiological Perspective".
- 22 sameAs 22.
- 22 abstract "The infectious disease domain brings together many practitioners working at different levels of granularity. And thus, they have different perspectives (biology, clinic and epidemiology) on the same phenomenon. Biomedical perspective deals with pathogens (e.g. life cycle) while clinical perspective deals with hosts (e.g. healthy or infected by the pathogen). In an epidemiological perspective, an infectious disease is characterized according to the way (causes, contamination process, etc.) it spreads in a population over space and time. This knowledge is then used in epidemiological monitoring systems to control the evolution and to prevent the emergence of disease spreading by implementing monitoring systems. In this poster we provide an ontological analysis of the epidemiological monitoring domain that aims to show how an Infectious Disease Ontology can support an infectious disease spreading crisis management in a various ways and at different phases of the monitoring process.".
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- 22 title "A Study of an Infectious Disease Ontology: the Epidemiological Perspective".
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- item-1 hasContent gaoussou-camara.
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- item-2 hasContent sylvie-despres.
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- 23 creator marcus-nitzschke.
- 23 creator sebastian-hellmann.
- 23 type InProceedings.
- 23 label "A Systematic Review about the Academic Impact of DBpedia".
- 23 sameAs 23.
- 23 abstract "In 2009, there was a large survey to collect journal articles and conference papers concerning the Wikipedia project. The findings of this survey were published, but are, as of now, only partially analyzed. The results showed a continuous growth of the number of journal articles related to Wikipedia. The number of conference papers grew until 5 years after the founding, but afterwards it began to decrease year by year. With these numbers in mind, we began our survey and started to interpret the data and find reasons for these characteristics. The poster will show the results of a systematic review of journal articles and conference papers about the DBpedia project. DBpedia extracts structured content from Wikipedia and republishes this content in a semantically understandable way. This allows one to ask comprehensive and sophisticated questions on top of the Wikipedia data. DBpedia is one of the most prominent data sets in the Linked Open Data cloud and has been used in a plethora of articles, since its foundation in 2007. The methodology comprises three main steps: (1) the data retrieval, (2) processing and (3) analysis. The process of data retrieval included four sources: Google Scholar, Arnetminer, the Semantic Web Conference Corpus and a manual research. We based our work on criteria developed in the Wikipedia study. The main criterion was that the term dbpedia occurs in the title or – if supported by the source – the abstract of the publication. Furthermore, we reduced the amount of publications to only match conference papers and journal articles, which were all peer reviewed.".
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- item-1 hasContent marcus-nitzschke.
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- item-2 hasContent sebastian-hellmann.
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- 24 creator alex-johansson.
- 24 creator eero-hyvoenen.
- 24 creator henri-ylikotila.
- 24 creator jouni-tuominen.
- 24 creator osma-suominen.
- 24 type InProceedings.
- 24 label "Vocabulary Services Based on SPARQL Endpoints: ONKI Light on SPARQL".
- 24 sameAs 24.
- 24 abstract "Vocabularies are an integral part of Linked Data (LD). They are published as browsable services for humans, as data dumps, as LD services, and as SPARQL endpoints for machines. Vocabulary services, such as concept lookup via term searches and hierarchical browsing, are used by indexers describing documents and searchers looking for suitable keywords. Basing vocabulary services on SPARQL endpoints containing SKOS vocabularies brings several benefits. We present the ONKI Light on SPARQL system, demonstrating how vocabulary services can be implemented using only SPARQL endpoints.".
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- 24 title "Vocabulary Services Based on SPARQL Endpoints: ONKI Light on SPARQL".
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