Abstract
Linked Open Data illustrates the concept that provides an optimum solution for information and dissemination of data, through the representation of the data in an open machine-readable format and to interlink it from diverse repositories to enable diverse usage scenarios for both humans and machines. The pharmaceutical/drug industry was among the first that validated the applicability of the approach for interlinking and publishing open linked data. This paper examines in detail the process of building Linked Data application taking into consideration the possibility of reusing recently published datasets and tools. Main conclusions derived from this study are that making drug datasets accessible and publish it in an open manner in linkable format adds great value by integration to other notable datasets. Yet, open issues arose clearly when trying to apply the approach to datasets coded in languages other than English, for instance, in Arabic languages.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Halpin, H.: Social Semantics: The Search for Meaning on the Web. Semantic Web and Beyond, vol. 13. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-1885-6
Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Sci. Am. (2001)
Berners-Lee, T.: Design issues: Linked Data. http://www.w3.org/DesignIssues/LinkedData.html. Accessed 1 May 2019
Jentzsch A., et al.: Linking open drug data. In: Triplification Challenge of the International Conference on Semantic Systems (2009)
W3C, Best Practices for Publishing Linked Data (2016). http://www.w3.org/TR/ld-bp/. Accessed 1 May 2019
Hyland, B., Wood, D.: The joy of data: a cookbook for publishing linked government data on the web. In: Wood, D. (ed.) Linking Government Data, pp. 3–26. Springer, New York (2011). https://doi.org/10.1007/978-1-4614-1767-5_1
Hausenblas, M.: Linked Data Life Cycles (2016). http://www.slideshare.net/mediasemanticweb/linked-data-life-cycles
Villazón-Terrazas, B., Vilches-Blázquez, L.M., Corcho, O., Gómez-Pérez, A.: Methodological guidelines for publishing government linked data. In: Wood, D. (ed.) Linking Government Data. Springer, New York, NY (2011). https://doi.org/10.1007/978-1-4614-1767-5_2
Auer, S., et al.: Managing the life-cycle of linked data with the LOD2 stack. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012. LNCS, vol. 7650, pp. 1–16. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35173-0_1
Jovanovik, M., Trajanov, D.: Consolidating drug data on a global scale using linked data. J. Biomed. Semant. 8(1), 3 (2017)
Janev, V., Mijović, V., Milosević, U., Vraneš, S.: Linked data apps: lessons learned. In: Trajanov, D., Bakeva, V. (eds.) ICT Innovations 2017 Web Proceedings, Communications in Computer and Information Science book series (CCIS, volume 778) (2017). ISSN 1865-0937
WebTeb. https://www.webteb.com/aboutusen
Altibbi. https://www.altibbi.com/
esaaf. https://www.123esaaf.com/
Kontokostas, D., Westphal, P., Auer, S., Hellmann, S., Lehmann, J., Cornelissen, R.: Test driven evaluation of linked data quality. In: Proceeding of the 23rd International Conference on World Wide Web, New York, NY, USA, pp. 747–758 (2014). http://dx.doi.org/10.1145/2566486.2568002
Zaveri, A., et al.: User-driven quality evaluation of DBpedia. In: Proceedings of the 9th International Conference on Semantic Systems, New York, NY, USA, pp. 97–104 (2013)
Zaveri, A., Rula, A., Maurino, A., Pietrobon, R., Lehmann, J., Auer, S.: Quality assessment for linked data: a survey. Semant. Web Interoperability Usability Appl. 7(1), 63–93 (2016). https://doi.org/10.3233/SW-150175
Radulović, F., Mihindukulasooriya, N., García-Castro, R., Gómez-Pérez, A.: A comprehensive quality model for linked data. Semant. Web Interoperability Usability Appl. 9(1), 3–24 (2018). https://doi.org/10.3233/SW-170267. Special issue on Quality Management of Semantic Web Assets (Data, Services and Systems)
Lackshen, G., Janev, V., Vraneš, S.: Quality assessment of Arabic DBpedia. In: Proceedings of 8th International Conference on Web Intelligence, Mining and Semantics, 25–27 June 2018, Novi Sad, Serbia. ACM, New York (2018). https://doi.org/10.1145/3227609.3227675
Acknowledgments
The research presented in this paper is partly financed by the Ministry of Science and Technological Development of the Republic of Serbia (SOFIA project, Pr. No: TR-32010) and partly by the EU project LAMBDA (GA No. 809965).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lakshen, G., Janev, V., Vraneš, S. (2019). Linking Open Drug Data: Lessons Learned. In: Saeed, K., Chaki, R., Janev, V. (eds) Computer Information Systems and Industrial Management. CISIM 2019. Lecture Notes in Computer Science(), vol 11703. Springer, Cham. https://doi.org/10.1007/978-3-030-28957-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-28957-7_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-28956-0
Online ISBN: 978-3-030-28957-7
eBook Packages: Computer ScienceComputer Science (R0)