Browse > Article
http://dx.doi.org/10.1633/JISTaP.2018.6.4.4

Topics and Trends in Metadata Research  

Oh, Jung Sun (School of Information and Library Science, University of North Carolina at Chapel Hill)
Park, Ok Nam (Department of Library and Information Science, Sangmyung University)
Publication Information
Journal of Information Science Theory and Practice / v.6, no.4, 2018 , pp. 39-53 More about this Journal
Abstract
While the body of research on metadata has grown substantially, there has been a lack of systematic analysis of the field of metadata. In this study, we attempt to fill this gap by examining metadata literature spanning the past 20 years. With the combination of a text mining technique, topic modeling, and network analysis, we analyzed 2,713 scholarly papers on metadata published between 1995 and 2014 and identified main topics and trends in metadata research. As the result of topic modeling, 20 topics were discovered and, among those, the most prominent topics were reviewed in detail. In addition, the changes over time in the topic composition, in terms of both the relative topic proportions and the structure of topic networks, were traced to find past and emerging trends in research. The results show that a number of core themes in metadata research have been established over the past decades and the field has advanced, embracing and responding to the dynamic changes in information environments as well as new developments in the professional field.
Keywords
topic modeling; metadata research; research trends; library and information science;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Boyd, K., & King, D. (2006). South Carolina goes digital: The creation and development of the University of South Carolina’s Digital Activities Department. OCLC Systems & Services, 22(3), 179-191.   DOI
2 Cho, J. (2013). The recent trends of information organization research in Japan and Korea. Library Collections, Acquisitions, and Technical Services, 37(3-4), 107-117.   DOI
3 Chuttur, M. Y. (2012). An experimental study of metadata training effectiveness on errors in metadata records. Journal of Library Metadata, 12(4), 372-395.   DOI
4 Chuttur, M. Y. (2014). Investigating the effect of definitions and best practice guidelines on errors in Dublin Core metadata records. Journal of Information Science, 40(1), 28-37.   DOI
5 Conners, D. (2008). A ghost in the catalog: The gradual obsolescence of the main entry. The Serials Librarian, 55(1-2), 85-97.   DOI
6 Cumming, K. (2007). Purposeful data: The roles and purposes of recordkeeping metadata. Records Management Journal, 17(3), 186-200.   DOI
7 Danskin, A. (2014). Implementing RDA at the British Library. CILIP Update, 40-41.
8 Daud, A. (2012). Using time topic modeling for semanticsbased dynamic research interest finding. Knowledge- Based Systems, 26, 154-163.   DOI
9 Aktas, M. S., Fox, G. C., & Pierce, M. (2010). A federated approach to information management in grids. International Journal of Web Services Research, 7(1), 65-98.   DOI
10 Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84.   DOI
11 Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022.
12 Blessinger, K., & Hrycaj, P. (2010). Highly cited articles in library and information science: An analysis of content and authorship trends. Library & Information Science Research, 32(2), 156-162.   DOI
13 Feicheng, M., & Yating, L. (2014). Utilising social network analysis to study the characteristics and functions of the co-occurrence network of online tags. Online Information Review, 38(2), 232-247.   DOI
14 Emery, J. (2007). Ghosts in the machine: The promise of electronic resource management tools. The Serials Librarian, 51(3-4), 201-208.   DOI
15 Evans, J. (2007). Evaluating the recordkeeping capabilities of metadata schemas. Archives and Manuscripts, 35(2), 56-84.
16 Evans, J., & Rouche, N. (2004). Utilizing systems development methods in archival systems research: Building a metadata schema registry. Archival Science, 4(3-4), 315-334.   DOI
17 Feick, T., Henderson, H., & England, D. (2011). One identifier: Find your oasis with NISO's I2 (institutional identifiers) standard. The Serials Librarian, 60(1-4), 213-222.   DOI
18 Feinerer, I., & Hornik, K. (2014). tm: Text Mining Package: A framework for text mining applications within R. Retrieved September 22, 2018 from http://CRAN.R-project.org/package=tm.
19 Ferris, A. M. (2002). Cataloging internet resources using MARC21 and AACR2: Online training for working catalogers. Cataloging & Classification Quarterly, 34(3), 339-353.   DOI
20 Greifeneder, E. (2014, Semptember). Trends in information behaviour research. Paper presented at ISIC: the information behaviour conference (part 1), Leeds, United Kingdom.
21 Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(Suppl 1), 5228-5235.
22 Grun, B., & Hornik, K. (2011). topicmodels: An R package for fitting topic models. Journal of Statistical Software, 40(13), 1-30.
23 Julien, H., Pecoskie, J. L., & Reed, K. (2011). Trends in information behavior research, 1999-2008: A content analysis. Library & Information Science Research, 33(1), 19-24.   DOI
24 Hall, D., Jurafsky, D., & Manning, C. D. (2008). Studying the history of ideas using topic models. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (pp. 363-371). Hawaii: Association for Computational Linguistics.
25 Han, M. J., & Hswe, P. (2011). The evolving role of the metadata librarian. Library Resources & Technical Services, 54(3), 129-141.   DOI
26 Hunter, J. (2003). Working towards MetaUtopia: A survey of current metadata research. Library Trends, 52(2), 318-344.
27 Kanellopoulos, D. N., & Kotsiantis, S. B. (2007). Semantic web: A state of the art survey. International Review on Computer and Software, 2(5), 428-442.
28 Lagace, N., Breeding, M., Romano Reynolds, R., & Han, N. (2013). Everyone’s a player: Creation of standards in a fast-paced shared world. The Serials Librarian, 64(1-4), 158-166.   DOI
29 Lalitha, P. (2009). Importance of digitization of cultural and heritage materials. SRELS Journal of Information Management, 46(3), 249-266.   DOI
30 McCallum, A. (2002). MALLET: A Machine Learning for Language Toolkit. Retrieved September 22, 2018 from http://mallet.cs.umass.edu.
31 Medeiros, N. (2003). A pioneering spirit: Using administrative metadata to manage electronic resources. OCLC Systems and Services, 19(3), 86-88.   DOI
32 Mimno, D., & McCallum, A. (2008). Topic models conditioned on arbitrary features with dirichletmultinomial regression. In Proceedings of 24th Conference on Uncertainty in Artificial 1 Intelligence (pp. 411-418). Arlington: AUAI Press.
33 Park, J. R. (2009). Metadata quality in digital repositories: A survey of the current state of the art. Cataloging & Classification Quarterly, 47(3-4), 213-228.   DOI
34 Mimno, D., McCallum, A., & Mann, G. S. (2006). Bibliometric impact measures leveraging topic analysis. In Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital libraries (JCDL '06) (pp. 65-74). New York: ACM.
35 Mullen, A. (2001). GILS metadata initiatives at the state level. Government Information Quarterly, 18(3), 167-180.   DOI
36 Palmer, C. L., Zavalina, O. L., & Mustafoff, M. (2007, June). Trends in metadata practices: A longitudinal study of collection federation. In Proceedings of the 7th ACM/ IEEE-CS Joint Conference on Digital Libraries (pp. 386-395). New York: ACM.
37 Park, J. R., & Tosaka, Y. (2010). Metadata quality control in digital repositories and collections: Criteria, semantics, and mechanisms. Cataloging & Classification Quarterly, 48(8), 696-715.   DOI
38 Patra, S. K., Bhattacharya, P., & Verma, N. (2006). Bibliometric study of literature on bibliometrics. DESIDOC Journal of Library & Information Technology, 26(1), 27-32.   DOI
39 Pattuelli, M. C. (2010). Knowledge organization landscape: A content analysis of introductory courses. Journal of Information Science, 36(6), 812-822.   DOI
40 Qin, J., & Paling, S. (2001). Converting a controlled vocabulary into an ontology: The case of GEM. Information Research: An International Electronic Journal, 6(2). Retrieved September 22, 2018 from http://www.informationr.net/ir/6-2/paper94.html.
41 R Core Team (2014). R: A language and environment for statistical computing. Vienna, Austria: The R Foundation for Statistical Computing.
42 Symonds, E., & May, C. (2009). Documenting local procedures: The development of standard digitization processes through the Dear Comrade project. Journal of Library Metadata, 9(3-4), 305-323.   DOI
43 Schottlaender, B. E. C. (2003). Why metadata? Why me? Why now? Cataloging and Classification Quarterly, 36(3-4), 19-29.   DOI
44 Shiri, A. (2003). Digital library research: Current developments and trends. Library Review, 52(5), 198-202.   DOI
45 Sievert, C., & Shirley, K. (2014). LDAvis: A method for visualizing and interpreting topics. In Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces (pp. 63-70). Baltimore: Association for Computational Linguistics.
46 Wakimoto, J. C. (2009). Scope of the library catalog in times of transition. Cataloging & Classification Quarterly, 47(5), 409-426.   DOI
47 Woodley, M. S. (2002). A digital library project on a shoestring. Library Collections, Acquisitions, and Technical Services, 26(3), 199-206.   DOI
48 Yague, M. I., Mana, A., & Lopez, J. (2005). A metadatabased access control model for web services. Internet Research, 15(1), 99-116.   DOI
49 Yeh, J., Chen, C., Sie, S., & Liu, C. (2014). X-System: An extensible digital library system for flexible and multipurpose contents management. International Journal of Digital Library Systems, 4(1), 25-40.   DOI
50 Zeng, M. L., & Qin, J. (2016). Metadata (2nd ed.). Chicago: American Library Association.