The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Big data, bigger dilemmas: A critical review
Abstract
The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain‐specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention—autonomy, opacity, generativity, disparity, and futurity—leading to questions and ideas for moving beyond dilemmas.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Burt, R. S. (1992) · doi:10.4159/9780674029095 · Cited by 9,093
Wing, J. M. (2006) · Communications of the ACM · doi:10.1145/1118178.1118215 · Cited by 8,102
Power failure: why small sample size undermines the reliability of neuroscience
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3475 · Cited by 7,641 · cited 1×
“In such samples, a change in a single unit can reverse the significance and affect the reproducibility of results (Button et al., 2013).”
BackgroundSimmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567
Statistical physics of social dynamics
Castellano, C., Fortunato, S., & Loreto, V. (2009) · Reviews of Modern Physics · doi:10.1103/revmodphys.81.591 · Cited by 4,119
FILTER BUBBLE: Wie wir im Internet entmündigt werden
Pariser, E. (2012) · doi:10.3139/9783446431164 · Cited by 1,849
Terranova, T. (2000) · Social Text · doi:10.1215/01642472-18-2_63-33 · Cited by 1,749
The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant
Gelman, A., & Stern, H. (2006) · The American Statistician · doi:10.1198/000313006x152649 · Cited by 1,407
Grounded Cognition: Past, Present, and Future: Topics in Cognitive Science
Barsalou, L. W. (2010) · Topics in Cognitive Science · doi:10.1111/j.1756-8765.2010.01115.x · Cited by 993
Erroneous analyses of interactions in neuroscience: A problem of significance
Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E.-J. (2011) · Nature Neuroscience · doi:10.1038/nn.2886 · Cited by 864
Research works printed but not linked: 114
- Abbott A., 2001, Chaos of disciplines
- Ackerman A.(2007 October 9).Google IBM forge computing program: Universities get access to big cluster computers. San Jose Mercury News Online Edition. Retrieved fromhttp://www.mercurynews.com/ci_7124839
- Anonymous, 2008, Community cleverness required [Editorial], Nature, 455, 1
- Anonymous, 2010, Data, data everywhere, The Economist, 394, 3
- Arnold S.E., 2011, Big Data: The new information challenge, Online, 27
- 10.1525/hsns.2010.40.2.183 · DOI · Paper page
- Bambauer J.Y., 2012, The new intrusion, Notre Dame Law Review, 88, 205
- Bergstein B.(2013 February 20).The problem with our data obsession. MIT Technology Review. Retrieved fromhttp://www.technologyreview.in/computing/42410/?mod=more
- Berry D.M.(2011)The philosophy of software: Code and mediation in the digital age London:Palgrave Macmillan. · DOI · Paper page
- Big Data: A Workshop Report. (2012).Washington DC: National Academies Press. Retrieved fromhttp://www.nap.edu/catalog.php?record_id=13541
- Bollier D., 2010, The promise and peril of big data
- 10.1007/s10767-006-9006-9 · DOI · Paper page
- 10.1002/asi.22634 · DOI · Paper page
- 10.1068/b3302t · DOI
- boyd d. &Crawford K.(2011).Six provocations for Big Data. Paper presented at the Oxford Internet Institute: A decade in internet time: Symposium on the dynamics of the internet and society. Retrieved fromhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=1926431
- 10.1080/1369118X.2012.678878 · DOI · Paper page
- 10.1002/asi.20883 · DOI
- 10.1016/j.shpsc.2011.10.007 · DOI
- Cameron W.B., 1963, Informal sociology: A casual introduction to sociological thinking
- 10.1147/sj.442.0249 · DOI
- Chakrabarti S., 2009, Data mining: Know it all
- 10.7208/chicago/9780226162775.001.0001 · doi:10.7208/chicago/9780226162775.001.0001
- Chen C., 2006, Information visualization: Beyond the horizon
- Crawford K., 2014, Big data and due process: Toward a framework to redress predictive privacy harms, Boston College Law Review, 55, 93
- 10.1002/asi.22928 · doi:10.1002/asi.22928
- Davenport T. H., 2012, How “Big Data” is different, Sloan Management Review, 43
- Day R.E., 2014, Beyond bibliometrics: Metrics‐based evaluation of research
- De la Porta D., 2006, Social movements: An introduction
- Descartes R., 1913, The meditations and selections from the Principles of Reneì Descartes (1596–1650)
- Doctorow C., 2008, Welcome to the petacentre, Nature, 455, 17
- 10.1515/9780691233857 · DOI · Paper page
- Dwork C., 2013, It's not privacy, and it's not fair, Stanford Law Review, 66
- Edwards P.N., 2010, A vast machine: Computer models, climate data, and the politics of global warming
- 10.1017/CBO9780511802126 · DOI
- Ekbia H., The political economy of exploitation in a networked world, The Information Society
- Ekbia H., 2014, Introduction to the special issue “Regimes of information: Embeddedness as paradox.”, The Information Society
- 10.7560/IC48204 · doi:10.7560/ic48204
- 10.1186/gm239 · DOI
- Elliott M.S., 2008, Computerization movements and technology diffusion: From mainframes to computing
- Facebook. (2012).Quarterly report pursuant to section 13 or 15
- 10.1007/s13347-012-0093-4 · DOI
- 10.1111/j.1468-2303.2009.00500.x · DOI
- 10.1177/0163443709350375 · DOI
- 10.1007/s10502-005-2594-8 · doi:10.1007/s10502-005-2594-8
- 10.1177/0263276411423038 · DOI
- 10.1002/asi.5090140304 · DOI · Paper page
- 10.1162/leon.2008.41.5.479 · doi:10.1162/leon.2008.41.5.479
- 10.7208/chicago/9780226292144.001.0001 · DOI · Paper page
- 10.7551/mitpress/9302.003.0002 · DOI
- 10.1080/00220970209602058 · DOI
- Gobble M.M., 2013, Big Data: The next big thing in innovation, Research‐Technology Management, 64
- Goffman E., 1974, Frame analysis: An essay on the organization of experience
- Gooding P. Warwick C. &Terras M.(2012).The myth of the new: Mass digitization distant reading and the future of the book. Paper presented at the Digital Humanities 2012 conference University of Hamburg Germany. Retrieved fromhttp://www.dh2012.uni‐hamburg.de/conference/programme/abstracts/the‐myth‐of‐the‐new‐mass‐digitization‐distant‐reading‐and‐the‐future‐of‐the‐book/
- 10.7326/0003-4819-130-12-199906150-00008 · DOI · Paper page
- 10.1053/j.seminhematol.2008.04.003 · DOI · Paper page
- Hardt M., 2000, Empire
- 10.1145/1743546.1743567 · DOI · Paper page
- 10.5210/fm.v18i10.4860 · doi:10.5210/fm.v18i10.4860
- Hey T., 2009, The fourth paradigm: Data‐intensive scientific discovery
- 10.1108/03684921111160278 · doi:10.1108/03684921111160278
- 10.1038/455047a · DOI · Paper page
- Hume D., 1993, An enquiry concerning human understanding
- International Business Machines—IBM. (2013).IBM narrows big data skills gap by partnering with more than 1 000 global universities. (Press release). Retrieved fromhttp://www‐03.ibm.com/press/us/en/pressrelease/41733.wss#release
- 10.1145/1536616.1536632 · DOI · Paper page
- Jones C.A., 1998, Picturing science, producing art
- Kaisler S. Armour F. Espinosa J.A. &Money W.(2013).Big Data: Issues and challenges moving forward. InProceedings from the 46th Hawaii International Conference on System Sciences (HICSS'46)(pp.995–1004).Piscataway NJ:IEEE Computer Society. · DOI · Paper page
- Kallinikos J., 2013, The allure of big data, Mercury, 3, 40
- Kling R., 1995, Ecologies of knowledge: Work and politics in science and technology
- 10.1109/TPC.2007.908725 · DOI
- 10.1109/MIC.2013.10 · DOI
- Lau A. &Vande Moere A.(2007).Towards a model of information aesthetic visualization. InProceedings of the IEEE International Conference on Information Visualisation (IV'07) Zurich Switzerland(pp.87–92).Piscataway NJ:IEEE Computer Society. · DOI
- 10.1038/455028a · DOI · Paper page
- Ma K.‐L., 2009, Next generation visualization technologies: Enabling discoveries at extreme scale, SciDag Review, 12, 12
- 10.5210/fm.v18i10.4868 · DOI
- Mattioli M.(forthcoming).Disclosing Big Data. Minnesota Law Review 99.
- Mayer‐Schonberger V., 2013, Big Data: A revolution that will transform how we live, work, and think
- Merton R.K., 1973, The sociology of science: Theoretical and empirical investigations
- 10.1002/9781118562260 · DOI · Paper page
- 10.7208/chicago/9780226029009.001.0001 · DOI · Paper page
- Nafus D. &Sherman J.(under review).This one does not go up to eleven: The Quantified Self movement as an alternative big data practice. International Journal of Communication. Retrieved from:http://www.digital‐ethnography.net/storage/NafusShermanQSDraft.pdf
- O'Reilly Media, 2011, Big Data now
- Ohm P., 2010, Broken promises of privacy: Responding to the surprising failure of anonymization, UCLA Law Review, 57, 1701
- Pajarola R.(1998).Large scale terrain visualization using the restricted quadtree triangulation. InProceedings of the Conference Visualization'98(pp.19–26).Piscataway NJ:IEEE Computer Society. · doi:10.1109/visual.1998.745280
- 10.1006/jvlc.2002.0232 · DOI · Paper page
- Reichman J.H., 1997, Intellectual property rights in data?, Vanderbilt Law Review, 50, 51
- 10.1515/9781400846337 · DOI · Paper page
- Savage C. &Shear M.D.(2013 August 9).President moves to ease worries on surveillance.The New York Times. Retrieved fromhttp://www.nytimes.com/2013/08/10/us/politics/obama‐news‐conference.html?pagewanted=all
- Schelling T.C., 1978, Micromotives and macrobehaviors
- Schwartz P.M., 2011, The PII problem: Privacy and a new concept of personally identifiable information, New York University Law Review, 86, 1814
- Sennett R., 2006, The culture of the new capitalism
- 10.1002/asi.22655 · DOI
- Smythe D.W., 1981, Dependency road: Communications, capitalism, consciousness and Canada
- Solove D.J.(2013).Introduction: Privacy self‐management and the consent dilemma. Harvard Law Review 126. Retrieved fromhttp://www.harvardlawreview.org/issues/126/may13/Symposium_9475.php
- Spence R., 2001, Information visualization
- Stodden V. Hurlin C. &Perignon C.(2012).RunMyCode.Org: A novel dissemination and collaboration platform for executing published computational results. Retrieved fromhttp://ssrn.com/abstract=2147710 · doi:10.2139/ssrn.2147710
- 10.1016/j.shpsc.2011.10.009 · DOI
- Tene O., 2012, Privacy in the age of Big Data: A time for big decisions, Stanford Law Review Online, 64, 63
- Thusoo A. Shao Z. Anthony S. Borthakur D. Jain N. Sen Sarma J. … (2010).Data warehousing and analytics infrastructure at facebook. InProceedings of the 2010 international conference on Management of data—SIGMOD '10(p.1013).New York:ACM Press. · DOI · Paper page
- 10.1038/nrg2857-c1 · DOI
- 10.1086/606126 · DOI
- Tufte E.R., 1983, The visual display of quantitative information
- 10.1111/j.1467-954X.2012.002120.x · DOI
- 10.1093/acprof:oso/9780199278220.001.0001 · DOI · Paper page
- Vande Moere A.(2005).Form follows data: The symbiosis between design & information visualization. InProceedings of the International Conference on Computer‐Aided Architectural Design (CAADFutures) Vienna Austria(pp.167–176).Dordrecht Netherlands:Springer.
- 10.5210/fm.v18i10.4878 · DOI
- 10.1038/455022a · DOI
- Ware C., 2013, Information visualization: Perception for design
- 10.2307/1321160 · DOI
- Weber M., 2002, The Protestant ethic and the spirit of capitalism
- 10.1126/science.134.3473.161 · DOI · Paper page
- Weinberger D., 2012, Too big to know: Rethinking knowledge now that the facts aren't the facts, experts are everywhere, and the smartest person in the room is the room
- Weingart S., 2012, Avoiding traps. the scottbot irregular [Blog post]
- White T., 2012, Hadoop: The definitive guide
- 10.1007/978-1-4471-2804-5_12 · DOI
Cited by
How to improve firm performance using big data analytics capability and business strategy alignment?
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.08.018 · Cited by 1,624
Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017) · Tourism Management · doi:10.1016/j.tourman.2016.10.001 · Cited by 1,051
Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7347 · Cited by 881
Debating big data: a literature review on realizing value from big data
Günther, W. A., Rezazade Mehrizi, M. H., Huysman, M., & Feldberg, F. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.07.003 · Cited by 880
Algorithmic regulation: A critical interrogation
Yeung, K. (2018) · Regulation & Governance · doi:10.1111/rego.12158 · Cited by 842
Metadata
- Authors
- Ekbia, H., Mattioli, M., Kouper, I., Arave, G., Ghazinejad, A., Bowman, T., Suri, V. R., Tsou, A., Weingart, S., & Sugimoto, C. R.
- Venue
- Journal of the Association for Information Science and Technology
- Publisher
- Wiley
- Published
- 2014-12-31
- Volume
- 66
- Issue
- 8
- Pages
- 1523-1545
- ISSN
- 2330-1635 (ISSN-L)
- 2330-1643
- OpenAlex
- W1920344448
- Cited by
- 305
- References
- 15
- FWCI
- 50.80
- Type
- journal article
- Language
- en
- Open access
- closed
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Big data, bigger dilemmas: A critical review. https://app.cochat.ai/papers/10.1002/asi.23294
- The paper
- Ekbia, H., Mattioli, M., Kouper, I., Arave, G., Ghazinejad, A., Bowman, T., Suri, V. R., Tsou, A., Weingart, S., & Sugimoto, C. R. (2015). Big data, bigger dilemmas: A critical review. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.23294
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.