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DOI: 10.4230/LIPIcs.GIScience.2021.I.5

Search Facets and Ranking in Geospatial Dataset Search

Authors: Thomas Hervey, Sara Lafia, and Werner Kuhn

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract

This study surveys the state of search on open geospatial data portals. We seek to understand 1) what users are able to control when searching for geospatial data, 2) how these portals process and interpret a user’s query, and 3) if and how user query reformulations alter search results. We find that most users initiate a search using a text input and several pre-created facets (such as a filter for tags or format). Some portals supply a map-view of data or topic explorers. To process and interpret queries, most portals use a vertical full-text search engine like Apache Solr to query data from a content-management system like CKAN. When processing queries, most portals initially filter results and then rank the remaining results using a common keyword frequency relevance metric (e.g., TF-IDF). Some portals use query expansion. We identify and discuss several recurring usability constraints across portals. For example, users are typically only given text lists to interact with search results. Furthermore, ranking is rarely extended beyond syntactic comparison of keyword similarity. We discuss several avenues for improving search for geospatial data including alternative interfaces and query processing pipelines.

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Thomas Hervey, Sara Lafia, and Werner Kuhn. Search Facets and Ranking in Geospatial Dataset Search. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 5:1-5:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{hervey_et_al:LIPIcs.GIScience.2021.I.5,
  author =	{Hervey, Thomas and Lafia, Sara and Kuhn, Werner},
  title =	{{Search Facets and Ranking in Geospatial Dataset Search}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{5:1--5:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.5},
  URN =		{urn:nbn:de:0030-drops-130405},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.5},
  annote =	{Keywords: search, portal, discovery, GIR, facet, relevance, ranking}
}

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Short Paper

DOI: 10.4230/LIPIcs.COSIT.2019.10

Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper)

Authors: Sara Lafia, Jingyi Xiao, Thomas Hervey, and Werner Kuhn

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract

Access to public data in the United States and elsewhere has steadily increased as governments have launched geospatially-enabled web portals like Socrata, CKAN, and Esri Hub. However, data discovery in these portals remains a challenge for the average user. Differences between users' colloquial search terms and authoritative metadata impede data discovery. For example, a motivated user with expertise can leverage valuable public data about transportation, real estate values, and crime, yet it remains difficult for the average user to discover and leverage data. To close this gap, community dashboards that use public data are being developed to track initiatives for public consumption; however, dashboards still require users to discover and interpret data. Alternatively, local governments are now developing data discovery systems that use voice assistants like Amazon Alexa and Google Home as conversational interfaces to public data portals. We explore these emerging technologies, examining the application areas they are designed to address and the degree to which they currently leverage existing open public geospatial data. In the context of ongoing technological advances, we envision using core concepts of spatial information to organize the geospatial themes of data exposed through voice assistant applications. This will allow us to curate them for improved discovery, ultimately supporting more meaningful user questions and their translation into spatial computations.

Cite as

Sara Lafia, Jingyi Xiao, Thomas Hervey, and Werner Kuhn. Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 10:1-10:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{lafia_et_al:LIPIcs.COSIT.2019.10,
  author =	{Lafia, Sara and Xiao, Jingyi and Hervey, Thomas and Kuhn, Werner},
  title =	{{Talk of the Town: Discovering Open Public Data via Voice Assistants}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{10:1--10:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.10},
  URN =		{urn:nbn:de:0030-drops-111026},
  doi =		{10.4230/LIPIcs.COSIT.2019.10},
  annote =	{Keywords: data discovery, open public data, voice assistants, essential model, GIS}
}

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Documents authored by Hervey, Thomas

Search Facets and Ranking in Geospatial Dataset Search

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Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper)

Abstract

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