Scientometrics

, Volume 98, Issue 2, pp 927–943 | Cite as

Semantic linkages in research information systems as a new data source for scientometric studies

Article

Abstract

A growing number of research information systems use a semantic linkage technique to represent in explicit mode information about relationships between elements of its content. This practice is coming nowadays to a maturity when already existed data on semantically linked research objects and expressed by this scientific relationships can be recognized as a new data source for scientometric studies. Recent activities to provide scientists with tools for expressing in a form of semantic linkages their knowledge, hypotheses and opinions about relationships between available information objects also support this trend. The study presents one of such activities performed within the Socionet research information system with a special focus on (a) taxonomy of scientific relationships, which can exist between research objects, especially between research outputs; and (b) a semantic segment of a research e-infrastructure that includes a semantic interoperability support, a monitoring of changes in linkages and linked objects, notifications and a new model of scientific communication, and at last—scientometric indicators built by processing of semantic linkages data. Based on knowledge what is a semantic linkage data and how it is stored in a research information system we propose an abstract computing model of a new data source. This model helps with better understanding what new indicators can be designed for scientometric studies. Using current semantic linkages data collected in Socionet we present some statistical experiments, including examples of indicators based on two data sets: (a) what objects are linked and (b) what scientific relationships (semantics) are expressed by the linkages.

Keywords

Research information system Scientific information objects Semantic linkages New data source Scientometric studies 

JEL Classification

C6 C8 

References

  1. Barrueco, J. M., & Krichel, T. (2005). Building an autonomous citation index for GL: RePEc, the economics working papers case. The Grey Journal, 1(2), 91–97.Google Scholar
  2. CERIF 1.3 Semantics: Research vocabulary. (2012). CERIF Task Group, euroCRIS. http://www.eurocris.org/Uploads/Web%20pages/CERIF-1.3/Specifications/CERIF1.3_Semantics.pdf.
  3. CERIF 1.3 Vocabulary. (2012). CERIF Task Group, euroCRIS. http://www.eurocris.org/Uploads/Web%20pages/CERIF-1.3/Semantics/CERIF1.3_Vocabulary.xls.
  4. Dix, A., Levialdi, S., & Malizia, A. (2006). Semantic halo for collaboration tagging systems. In the Social Navigation and Community-Based Adaptation Technologies Workshop-June 20th.Google Scholar
  5. Galassini, C., Malizia, A., & Bellucci, A. (2011). An approach for developing intelligent systems for sentiment analysis over social networks. In J. F. Whidborne, P. Willis, G. Montana (Eds.), Intelligent Systems and Control/742: Computational Bioscience, Cambridge, United Kingdom, July 11–13.Google Scholar
  6. Groth, P., Gibson, A., & Velterop, J. (2010): The anatomy of a nano-publication. Information Services and Use 30(1/2). http://iospress.metapress.com/content/ftkh21q50t521wm2/.
  7. Jörg, B., Ruiz-Rube, I., Sicilia, M., DVOŘÁK, J., Jeffery, K., Hoellrigl, T., et al. (2012a). Connecting closed world research information systems through the linked open data web. International Journal of Software Engineering and Knowledge Engineering, 22(3), 345–364.CrossRefGoogle Scholar
  8. Jörg, B., Jeffery, K. G., Dvorak, J., Houssos, N., Asserson, A., van Grootel, G., et al. (2012b). CERIF 1.3 Full Data Model (FDM): Introduction and specification. euroCRIS. http://www.eurocris.org/Uploads/Web%20pages/CERIF-1.3/Specifications/CERIF1.3_FDM.pdf.
  9. Karlsson, S. (2011). About LogEc. http://logec.repec.org/about.htm.
  10. Kogalovsky, M., & Parinov, S. (2008). Metrics of online information spaces. Economics and Mathematical Methods, 44(2), (in Russian), authors’ version. http://socionet.ru/publication.xml?h=repec:rus:mqijxk:17.
  11. Kogalovsky, M., & Parinov, S. (2009). Scientometrics by using a citation type of linkages in Socionet system. Deposited by authors at Socionet (in Russian). http://socionet.ru/publication.xml?h=repec:rus:rssalc:web-32.
  12. Krichel, T., & Parinov, S. (2002). The RePEc database and its Russian partner Socionet. Russian Digital Libraries Journal. 5(2). http://www.elbib.ru/index.phtml?page=elbib/eng/journal/2002/part2/KP.
  13. Parinov, S. (2009). Electronic libraries development is a way to Open Science. In Proceedings of the XI All-Russian Research Conference “RCDL2009”, Petrozavodsk, Russia (in Russian), author’s version. http://socionet.ru/publication.xml?h=repec:rus:mqijxk:21.
  14. Parinov, S. (2010a). CRIS driven by research community: benefits and perspectives. In proceedings of the 10th International Conference on Current Research Information Systems. (2–5th June, pp. 119–130) Aalborg University, Denmark. http://socionet.ru/publication.xml?h=repec:rus:mqijxk:23.
  15. Parinov, S. (2010b). The electronic library: Using technology to measure and support Open Science. In Proceedings of the World Library and Information Congress: 76th IFLA General Conference and Assembly, Gothenburg, Sweden, 10–15 August. http://www.ifla.org/files/hq/papers/ifla76/155-parinov-en.pdf.
  16. Parinov, S. (2012a). Open Repository of Semantic Linkages. In Proceedings of 11th International Conference on Current Research Information Systems e-Infrastructure for Research and Innovations (CRIS 2012), Prague .http://socionet.ru/publication.xml?h=repec:rus:mqijxk:29.
  17. Parinov, S. (2012b). Towards a semantic segment of a research e-infrastructure: necessary information objects, tools and services. In J. M. Dodero, M. Palomo-Duarte, P. Karampiperis, (Eds.), Metadata and Semantics Research, Communications in Computer and Information Science (Vol. 343, pp. 133–145). Springer. http://socionet.ru/pub.xml?h=RePEc:rus:mqijxk:30.
  18. Parinov, S., Lyapunov V., & Puzyrev R. (2003). Socionet system as a platform for developing information resources and online services for researchers. Russian Digital Libraries Journal, 1(6), (in Russian). http://www.elbib.ru/index.phtml?page=elbib/rus/journal/2003/part1/PLP.
  19. Parinov, S., & Kogalovsky, M. (2011). A technology for semantic structuring of scientific digital library content. In Proceeding of the XIIIth All-Russian Scientific Conference RCDL 2011. Digital Libraries: Advanced Methods and Technologies, Digital Collections, October 19–22, pp. 94–103. Voronezh State University (in Russian). http://socionet.ru/publication.xml?h=repec:rus:mqijxk:28.
  20. Parinov, S., & Krichel, T. (2004). RePEc and Socionet as partners in a changing digital library environment, 1997–2004 and beyond. In Russian Conference on Digital Libraries, Pushchino, Russia, http://eprints.rclis.org/archive/00001830/01/bonn.pdf.
  21. Shotton, D. (2010a). Use of CiTO in CiteULike. http://opencitations.wordpress.com/2010/10/21/use-of-cito-in-citeulike/.
  22. Shotton, D. (2010b). Introduction the semantic publishing and referencing (SPAR) ontologies. http://opencitations.wordpress.com/2010/10/14/introducing-the-semantic-publishing-and-referencing-spar-ontologies/.
  23. Shotton, D. (2010c). CiTO, the citation typing ontology. Journal of Biomedical Semantics, 1(Suppl 1): S6. http://www.jbiomedsem.com/content/1/S1/S6.
  24. Shotton, D., & Peroni, S. (2011). DoCO, the document components ontology. 17/02/2011. http://purl.org/spar/doco/.
  25. Shum, S. B., Clark T., de Waard A., Groza T., Handschuh S., & Sandor A. (2010). Scientific discourse on the semantic web: A survey of models and enabling technologies. Semantic Web Journal: Interoperability, Usability, Applicability. Special Issue on Survey Articles, Ed. Pascal Hitzler, http://www.semantic-web-journal.net/content/scientific-discourse-semantic-web-survey-models-and-enabling-technologies.
  26. Small, H. (2011). Interpreting maps of science using citation context sentiments: a preliminary investigation. Scientometrics, Springer Netherlands, 87(2), 373–388.Google Scholar
  27. SKOS (2009). SKOS Simple Knowledge Organization System Reference. W3C Recommendation 18 August 2009. http://www.w3.org/TR/skos-reference/.
  28. Socionet Stats (in Russian). http://www.socionet.ru/stats.xml.
  29. SWAN (2009). Semantic Web Applications in Neuromedicine (SWAN) Ontology. W3C Interest Group Note 20 October 2009. http://www.w3.org/TR/2009/NOT-ehcls-swan-20091020/.

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2013

Authors and Affiliations

  1. 1.Central Economics and Mathematics InstituteRussian Academy of SciencesMoscowRussia
  2. 2.Market Economy InstituteRussian Academy of SciencesMoscowRussia

Personalised recommendations