The DOI matches its Crossref record.
The Fourth Paradigm – Data-Intensive Scientific Discovery
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Citations
Cited by
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Unique in the Crowd: The privacy bounds of human mobility
de Montjoye, Y.-A., Hidalgo, C. A., Verleysen, M., & Blondel, V. D. (2013) · Scientific Reports · doi:10.1038/srep01376 · Cited by 1,645
Data Sharing by Scientists: Practices and Perceptions
Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., Manoff, M., & Frame, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021101 · Cited by 1,432
Learning Analytics: The Emergence of a Discipline
Siemens, G. (2013) · American Behavioral Scientist · doi:10.1177/0002764213498851 · Cited by 1,284
Metadata
- Authors
- Hey, T.
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 1-1
- ISSN
- 1865-0929 (ISSN-L)
- 1865-0937
- OpenAlex
- W1548849615
- Cited by
- 1,585
- References
- 0
- FWCI
- 154.38
- Type
- conference paper
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Fourth Paradigm – Data-Intensive Scientific Discovery. https://app.cochat.ai/papers/10.1007/978-3-642-33299-9_1
- The paper
- Hey, T. (2012). The Fourth Paradigm – Data-Intensive Scientific Discovery. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-642-33299-9_1
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.
