The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.
Big Scholarly Data: A Survey
Abstract
With the rapid growth of digital publishing, harvesting, managing, and analyzing scholarly information have become increasingly challenging. The term Big Scholarly Data is coined for the rapidly growing scholarly data, which contains information including millions of authors, papers, citations, figures, tables, as well as scholarly networks and digital libraries. Nowadays, various scholarly data can be easily accessed and powerful data analysis technologies are being developed, which enable us to look into science itself with a new perspective. In this paper, we examine the background and state of the art of big scholarly data. We first introduce the background of scholarly data management and relevant technologies. Second, we review data analysis methods, such as statistical analysis, social network analysis, and content analysis for dealing with big scholarly data. Finally, we look into representative research issues in this area, including scientific impact evaluation, academic recommendation, and expert finding. For each issue, the background, main challenges, and latest research are covered. These discussions aim to provide a comprehensive review of this emerging area. This survey paper concludes with a discussion of open issues and promising future directions.
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Cites
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Artificial Intelligence in the 21st Century
Liu, J., Kong, X., Xia, F., Bai, X., Wang, L., Qing, Q., & Lee, I. (2018) · IEEE Access · doi:10.1109/access.2018.2819688 · Cited by 270
Self-citationScholarly knowledge graphs through structuring scholarly communication: a review
Verma, S., Bhatia, R., Harit, S., & Batish, S. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-022-00806-6 · Cited by 78
A compression-diffusion-permutation strategy for securing image
Huang, H., He, X., Xiang, Y., Wen, W., & Zhang, Y. (2018) · Signal Processing · doi:10.1016/j.sigpro.2018.04.014 · Cited by 48
Unveiling Scholarly Communities over Knowledge Graphs
Vahdati, S., Palma, G., Nath, R. J., Lange, C., Auer, S., & Vidal, M.-E. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-00066-0_9 · Cited by 16
Leveraging Disruptive Technologies and Systems Thinking Approach at Higher Education Institutions
Mafu, M. (2023) · The Sustainable University of the Future · doi:10.1007/978-3-031-20186-8_2 · Cited by 3
Metadata
- Authors
- Xia, F., Wang, W., Bekele, T. M., & Liu, H.
- Venue
- IEEE Transactions on Big Data
- Published
- 2017-03-01
- Volume
- 3
- Issue
- 1
- Pages
- 18-35
- ISSN
- 2332-7790 (ISSN-L)
- OpenAlex
- W2570427954
- Cited by
- 266
- References
- 112
- FWCI
- 36.59
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
