Kimberly Douglass
- Information Systems top 1%
- Information Systems and Management top 0.5%
- Management Science and Operations Research top 2%
- Statistics, Probability and Uncertainty top 2%
- Ecological Modeling top 5%
- Co-authors
- Carol TenopirSuzie AllardMike FrameLei WuEleanor J. ReadMaribeth ManoffArsev Umur AydınoğluRobert B. Cook
- Topics
- Research Data Management Practices (4 papers)Data Quality and Management (3 papers)Library Science and Administration (3 papers)
- Partner nations
- United States
In The Last Decade
Kimberly Douglass
9 papers receiving 995 citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Information Systems 713
- Information Systems and Management 560
- Management Science and Operations Research 333
- Statistics, Probability and Uncertainty 122
- Ecological Modeling 118
Countries citing papers authored by Kimberly Douglass
This map shows the geographic impact of Kimberly Douglass's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kimberly Douglass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kimberly Douglass more than expected).
Fields of papers citing papers by Kimberly Douglass
This network shows the impact of papers produced by Kimberly Douglass. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kimberly Douglass. The network helps show where Kimberly Douglass may publish in the future.
Co-authorship network of co-authors of Kimberly Douglass
This figure shows the co-authorship network connecting the top 25 collaborators of Kimberly Douglass. A scholar is included among the top collaborators of Kimberly Douglass based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kimberly Douglass. Kimberly Douglass is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | |
| 4 | The role of federal libraries and federal librarians in research data services (RDS): An exploratory study | 0 |
| 5 | 20 | |
| 6 | 0 | |
| 7 | 31 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | Data Sharing by Scientists: Practices and Perceptionsbreakdown → | 905 |
| 11 | 97 | |
| 12 | 14 |
About Kimberly Douglass
Kimberly Douglass is a scholar working on Library and Information Sciences, Information Systems and Management and Conservation, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Research Data Management Practices (4 papers), Data Quality and Management (3 papers) and Library Science and Administration (3 papers). The work is most often cited by research in Information Systems and Management (560 citations), Information Systems (713 citations) and Ecological Modeling (118 citations). Kimberly Douglass has collaborated with scholars based in United States. Frequent co-authors include Carol Tenopir, Suzie Allard, Mike Frame, Lei Wu, Eleanor J. Read, Maribeth Manoff, Arsev Umur Aydınoğlu, Robert B. Cook, William K. Michener and Steve Kelling. Their work appears in journals such as PLoS ONE, Ecological Informatics and First Monday.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.