Abstract
Governments worldwide have been releasing their owned data recently for public usage and arising lots of novel applications and services. Issues on open data were also intensively discussed from researchers and practitioners. One of the key issues in adopting open data is the accessibility of the data, which are generally collectively provided in open data portals. Open data portals categorize open datasets according to their domains, providers, formats, and other properties for better accessibility of the data. However, these portals did not follow a conforming standard in establishing their categorization structures. In this work, we try to assess the goodness of categorization structures of open data portals automatically by investigating the coherence of the datasets in the same category. The detailed methodology is described but preliminary experiments on Taiwan’s open data portals are still undergoing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)
Open Knowledge Foundation: Open data handbook (2012). http://opendatahandbook.org/ (accessed May 15, 2015)
Pipino, L.L., Lee, Y.W., Wang, R.Y.: Data quality assessment. Communications of the ACM 45(4), 211–218 (2002)
Batini, C., Cappiello, C., Francalanci, C., Maurino, A.: Methodologies for data quality assessment and improvement. ACM Computing Surveys 41(3), 16:1–16:52 (2009)
Berners-Lee, T.: Linked data (2010). http://www.w3.org/DesignIssues/LinkedData.html (accessed July, 10 2014)
Zaveri, A., Rula, A., Maurino, A., Pietrobon, R., Lehmann, J., Auer, S.: Quality assessment for linked data: A survey. Semantic Web Journal (2015)
Behkamal, B.: Metrics-driven framework for lod quality assessment. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 806–816. Springer, Heidelberg (2014)
Knuth, M., Kontokostas, D., Sack, H.: Linked data quality: identifying and tackling the key challenges. In: Knuth, M., Kontokostas, D., Sack, H. (eds.) 1st Workshop on Linked Data Quality (LDQ). Number 1215 in CEUR Workshop Proceedings, Aachen (2014)
Calero, C., Caro, A., Piattini, M.: An applicable data quality model for Web portal data consumers. World Wide Web 11(4), 465–484 (2008)
Umbrich, J., Neumaier, S., Polleres, A.: Towards assessing the quality evolution of open data portals. In: Proceedings of ODQ2015: Open Data Quality: from Theory to Practice Workshop, Munich, Germany (2015)
Colpaert, P., Joye, S., Mechant, P., Mannens, E., Van de Walle, R.: The 5 stars of open data portals. In: Álvarez Sabucedo, L., Anido Rifón, L. (eds.) Proceedings of the 7th International Conference on Methodologies, Technologies and Tools Enabling e-Government, pp. 61–67. Universida de Vigo (2013)
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, HC., Lin, C.S., Yu, PH. (2015). Toward Automatic Assessment of the Categorization Structure of Open Data Portals. In: Wang, L., Uesugi, S., Ting, IH., Okuhara, K., Wang, K. (eds) Multidisciplinary Social Networks Research. MISNC 2015. Communications in Computer and Information Science, vol 540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48319-0_30
Download citation
DOI: https://doi.org/10.1007/978-3-662-48319-0_30
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48318-3
Online ISBN: 978-3-662-48319-0
eBook Packages: Computer ScienceComputer Science (R0)