By Sebastian Maneth
This publication constitutes the refereed convention complaints of the thirtieth British foreign convention on Databases, BICOD 2015 - previously often called BNCOD (British nationwide convention on Databases) - held in Edinburgh, united kingdom, in July 2015.
The 19 revised complete papers, awarded including 3 invited
keynotes and 3 invited lectures have been rigorously reviewed and chosen from 37 submissions. precise concentration of the convention has been "Data technology" and so the papers conceal a variety of subject matters concerning databases and data-centric computation.
Read or Download Data Science: 30th British International Conference on Databases, BICOD 2015, Edinburgh, UK, July 6-8, 2015, Proceedings PDF
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Extra info for Data Science: 30th British International Conference on Databases, BICOD 2015, Edinburgh, UK, July 6-8, 2015, Proceedings
Example text
The BioPortal1 open repository for biomedical ontologies is used to explore possible ontologies to integrate them with the LEMO system. org/. Applying NoSQL Databases for Integrating Web Educational Stores 33 users to get information about the ontologies or its content [18]. The LEMO system uses additional web services such as the annotator service provided by Bioportal for annotating and linking objects in the dataset. The ontologies used in the LEMO system so far are the Systematized Nomenclature of Medicine Clinical Terms SNOMED CT and the Medical Subject Headings MeSH.
We can notice that in SNOMED CT, only 11 % of the keywords annotated in the description were chosen as a subject, compared to a higher percentage of 26 % keywords in the description using MeSH. Q. Al Fayez and M. Joy (a) Subjects based on MeSH (b) Subjects based on SNOMED Fig. 3. Subject selection The LEMO dataset consists of different types of EMOs. Video and blog EMOs usually have shorter descriptions in their metadata fields if any. This affects the number of keywords annotated for EMOs from such types and that reflects on the number of subjects selected.
1 Discovering Subjects Using Ontologies After processing the keyword set for each EMO, subjects were selected from the keywords annotated for categorizing each EMO. The resulting sets of subjects selected for each EMO are variable in size. We calculated the total numbers of subjects selected in the LEMO dataset and compared them against the keywords set sizes. The results are detailed in Fig. 3a and b for the MeSH and SNOMED CT subject selections respectively. The percentage of keywords chosen as subject terms from the SNOMED CT annotated terms is less than the percentage from the MeSH annotated collection.