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DOI: 10.4230/LIPIcs.GISCIENCE.2018.9

Improving Discovery of Open Civic Data

Authors: Sara Lafia, Andrew Turner, and Werner Kuhn

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract

We describe a method and system design for improved data discovery in an integrated network of open geospatial data that supports collaborative policy development between governments and local constituents. Metadata about civic data (such as thematic categories, user-generated tags, geo-references, or attribute schemata) primarily rely on technical vocabularies that reflect scientific or organizational hierarchies. By contrast, public consumers of data often search for information using colloquial terminology that does not align with official metadata vocabularies. For example, citizens searching for data about bicycle collisions in an area are unlikely to use the search terms with which organizations like Departments of Transportation describe relevant data. Users may also search with broad terms, such as "traffic safety", and will then not discover data tagged with narrower official terms, such as "vehicular crash". This mismatch raises the question of how to bridge the users' ways of talking and searching with the language of technical metadata. In similar situations, it has been beneficial to augment official metadata with semantic annotations that expand the discoverability and relevance recommendations of data, supporting more inclusive access. Adopting this strategy, we develop a method for automated semantic annotation, which aggregates similar thematic and geographic information. A novelty of our approach is the development and application of a crosscutting base vocabulary that supports the description of geospatial themes. The resulting annotation method is integrated into a novel open access collaboration platform (Esri's ArcGIS Hub) that supports public dissemination of civic data and is in use by thousands of government agencies. Our semantic annotation method improves data discovery for users across organizational repositories and has the potential to facilitate the coordination of community and organizational work, improving the transparency and efficacy of government policies.

Cite as

Sara Lafia, Andrew Turner, and Werner Kuhn. Improving Discovery of Open Civic Data. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{lafia_et_al:LIPIcs.GISCIENCE.2018.9,
  author =	{Lafia, Sara and Turner, Andrew and Kuhn, Werner},
  title =	{{Improving Discovery of Open Civic Data}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{9:1--9:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.9},
  URN =		{urn:nbn:de:0030-drops-93376},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.9},
  annote =	{Keywords: data discovery, metadata, query expansion, interoperability}
}

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Improving Discovery of Open Civic Data

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