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SBE 2020: Submission Detail

ID Number: 186
Title: The Web of Linked Data: Realizing the Potential for the Social Sciences
Lead Author: Gregory, Arofan
Abstract: The Linked Data Web holds great promise for social science researchers, enabling efficient discovery of data and increasing the ease with which disparate datasets can be merged. Further, quantitative data sources can be easily connected with non-quantitative resources such as research papers. However, this vision will not be realized if best practice in documenting social science data is not combined with the use of the new technologies. The key to realizing the transformative potential of the Linked Data Web for SBE sciences is collaboration among technologists and data managers and producers, based on the emerging standard metadata models used for quantitative SBE data. The most prominent of these is the Data Documentation Initiative (DDI). If these models can be realized as standard ontologies for the publication of research data as Linked Data, then the wealth of SBE data found in data archives and in government organizations become discoverable and available to create new knowledge. Without such standard ontologies, the creation of generic tools for working with quantitative Linked Data will not be possible, and we will fail to realize the potential of the technology for the SBE sciences.
PDF: Gregory_Arofan_186.pdf

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