The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Data Alive! The Thinking Behind NVivo
Abstract
Rich data from qualitative research have been treated poorly by computers. Yet, plain text and static documents largely have been uncritically accepted as a price of coding. The new qualitative software from Qualitative Solutions and Research (QSR), NUD•IST Vivo (NVivo), challenges that assumption. This article explores the goals of rich data in qualitative research and the ways NVivo addresses these. Like its sibling software, NUD•IST4, NVivo supports code-based inquiry, searching, and theorizing combined with ability to annotate and edit documents. However, NVivo is designed for researchers who wish to display and develop rich data in dynamic documents. Documents can be imported and edited in rich text with hyperlinks to sound, image, and other files, but they also can be coded as finely as needed and the results of coding displayed, explored, and modeled. The final section offers a brief outline of these and other features of the new software.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Handbook of Qualitative Research.
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American Sociological Association
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From filing cabinet to computer
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Self-citationCloseness to Data: The Changing Goals of Qualitative Data Handling
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User's Mistake as Developer's Challenge: Designing the New NUD*IST
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Self-citation
Research works printed but not linked: 3
- Qualitative Solutions and Research, 1997, QSR NUD•IST rev. 4 user’s guide
- Richards, L., 1995, Computing and qualitative analysis, 105
- Richards, L., 1994, Handbook of qualitative research, 445
Cited by
Ringrose, J., Milne, B., Mishna, F., Regehr, K., & Slane, A. (2022) · Women's Studies International Forum · doi:10.1016/j.wsif.2022.102615 · Cited by 67
Ring, A., Jacoby, A., Baker, G., Holmes, E., Hughes, D., Kierans, C., & Marson, A. (2019) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2019.03.033 · Cited by 16
Metadata
- Authors
- Richards, L.
- Affiliations
- Western Sydney University (AU)
- Corresponding author
- Richards, Lyn
- Venue
- Qualitative Health Research
- Publisher
- SAGE Publications
- Published
- 1999-05
- Volume
- 9
- Issue
- 3
- Pages
- 412-428
- ISSN
- 1049-7323 (ISSN-L)
- 1552-7557
- OpenAlex
- W2135967363
- Cited by
- 164
- References
- 17
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 4 · 2023: 4 · 2022: 4 · 2021: 4 · 2020: 6 · 2019: 7 · 2018: 9 · 2017: 4 · 2016: 9 · 2015: 12 · 2014: 8 · 2013: 14 · 2012: 12
- FWCI
- 14.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Qualitative Health Research (publishedVersion)
- Topics
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Keywords
- NVivo, qualitative data analysis software, dynamic documents, coding, annotation, NUD*IST, qualitative research tools, theorizing
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 ›
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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.
