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Mahesh, Kavi
- Managing Research Data
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1 Centre for Knowledge Analytics and Ontological Engineering, PES University, Bengaluru, IN
1 Centre for Knowledge Analytics and Ontological Engineering, PES University, Bengaluru, IN
Source
Information Studies, Vol 21, No 1 (2015), Pagination: 1-6Abstract
It is becoming a common practice to publish data generated in research projects along with the results derived from the data. As more and more datasets are published, the digital library of the future needs an effective solution for managing repositories of both documents and datasets. Academic libraries may soon be expected to manage and provide access to research data in addition to books and periodicals. The technological needs of such a research data service suggest a model based on the use of semantic linking using the constructs of ontology, on top of data represented in the form of Linked Open Datasets.References
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- From Data to Knowledge Analytics:Capabilities and Limitations
Abstract Views :387 |
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Authors
Affiliations
1 KAnOE - Center for Knowledge Analytics and Ontological Engineering, PES University, Bangalore 560085, IN
1 KAnOE - Center for Knowledge Analytics and Ontological Engineering, PES University, Bangalore 560085, IN
Source
Information Studies, Vol 21, No 4 (2015), Pagination: 261-274Abstract
Data analytics is playing a central role in deriving useful information from large amounts of data available online in a variety of domains and applications. Analytics enploys a wide array of methods ranging from classical statistical techniques to those exploiting the visual and cognitive capabiUties of human users. In spite of all its capabilities, analytics at present seems to suffer from significant limitations in deahng with unstructured data and knowledge. This article explores the Umitations and defines key requirements to be met by fiiture developments in analytics. The article concludes with a sketch of tme knowledge analytics which is capable of delivering insights from knowledge structures, not just tabular data.Keywords
Analytics, Unstructured Data, Knowledge, Capabilities, Limitations.References
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