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International Conference on Web Reasoning and Rule Systems

RR 2015: Web Reasoning and Rule Systems pp 93–104Cite as

A Rule-based Framework for Creating Instance Data from OpenStreetMap

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9209))

Abstract

Reasoning engines for ontological and rule-based knowledge bases are becoming increasingly important in areas like the Semantic Web or information integration. It has been acknowledged however that judging the performance of such reasoners and their underlying algorithms is difficult due to the lack of publicly available datasets with large amounts of (real-life) instance data. In this paper we describe a framework and a toolbox for creating such datasets, which is based on extracting instances from the publicly available OpenStreetMap (OSM) geospatial database. To this end, we give a formalization of OSM and present a rule-based language to specify the rules to extract instance data from OSM data. The declarative nature of the approach in combination with external functions and parameters allows one to create several variants of the dataset via small modifications of the specification. We describe a highly flexible toolbox to extract instance data from a given OSM map and a given set of rules. We have employed our tools to create benchmarks that have already been fruitfully used in practice.

Supported by the Vienna Science and Technology Fund (WWTF) project ICT12-15, by the Austrian Science Fund (FWF) project P25207, and by the EU project Optique FP7-318338.

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Notes

  1. 1.

    http://www.openstreetmap.org.

  2. 2.

    E.g., visible in https://www.mapbox.com/osm-data-report/.

  3. 3.

    For clarity, we rename the expressions used in OSM.

  4. 4.

    See the detailed syntax, prerequisites, and tools on https://github.com/ghxiao/city-bench.

  5. 5.

    https://github.com/ghxiao/owl-toolkit.

  6. 6.

    http://www.dlvsystem.com/dlv/.

  7. 7.

    https://github.com/enaeseth/python-fp-growth.

  8. 8.

    https://github.com/ghxiao/city-bench/tree/master/benchmarks/rr2015.

  9. 9.

    Downloaded on the 1.10.14 from http://download.bbbike.org/osm/bbbike/.

  10. 10.

    http://www.kr.tuwien.ac.at/research/systems/dlvhex/.

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Author information

Authors and Affiliations

  1. Institute of Information Systems, Vienna University of Technology, Vienna, Austria

    Thomas Eiter, Patrik Schneider & Mantas Šimkus

  2. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    Guohui Xiao

  3. University of Aberdeen, Aberdeen, UK

    Jeff Z. Pan

  4. Vienna University of Economics and Business, Vienna, Austria

    Patrik Schneider

Authors
  1. Thomas Eiter
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  2. Jeff Z. Pan
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  3. Patrik Schneider
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  4. Mantas Šimkus
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  5. Guohui Xiao
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Corresponding author

Correspondence to Patrik Schneider .

Editor information

Editors and Affiliations

  1. University of California, Santa Cruz, USA

    Balder ten Cate

  2. National University of Ireland, Galway, Ireland

    Alessandra Mileo

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© 2015 Springer International Publishing Switzerland

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Eiter, T., Pan, J.Z., Schneider, P., Šimkus, M., Xiao, G. (2015). A Rule-based Framework for Creating Instance Data from OpenStreetMap . In: ten Cate, B., Mileo, A. (eds) Web Reasoning and Rule Systems. RR 2015. Lecture Notes in Computer Science(), vol 9209. Springer, Cham. https://doi.org/10.1007/978-3-319-22002-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-22002-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22001-7

  • Online ISBN: 978-3-319-22002-4

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