Matches in ScholarlyData for { ?s ?p 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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- 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.".