Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Data Sharing by Scientists: Practices and Perceptions
2011905 citationsCarol Tenopir, Suzie Allard et al.PLoS ONEprofile →
Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide
2015302 citationsCarol Tenopir, Elizabeth D. Dalton et al.PLoS ONEprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Mike Frame'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 Mike Frame with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike Frame more than expected).
This network shows the impact of papers produced by Mike Frame. 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 Mike Frame. The network helps show where Mike Frame may publish in the future.
Co-authorship network of co-authors of Mike Frame
This figure shows the co-authorship network connecting the top 25 collaborators of Mike Frame.
A scholar is included among the top collaborators of Mike Frame 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 Mike Frame. Mike Frame is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Allard, Suzie, et al.. (2018). Assisting geophysicists in data management: Perceptions and opportunities.. AGU Fall Meeting Abstracts. 2018.1 indexed citations
Tenopir, Carol, Elizabeth D. Dalton, Suzie Allard, et al.. (2015). Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide. PLoS ONE. 10(8). e0134826–e0134826.302 indexed citations breakdown →
9.
Volentine, Rachel, et al.. (2014). Usability testing to improve research data services..3 indexed citations
10.
Budden, Amber E, Mike Frame, Carol Tenopir, & Rachel Volentine. (2014). Usability analysis within The DataONE network of collaborators.. AGU Fall Meeting Abstracts. 2014.
Douglass, Kimberly, et al.. (2014). The role of federal libraries and federal librarians in research data services (RDS): An exploratory study.
13.
Tenopir, Carol, Suzie Allard, Kimberly Douglass, et al.. (2011). Data Sharing by Scientists: Practices and Perceptions. PLoS ONE. 6(6). e21101–e21101.905 indexed citations breakdown →
14.
Frame, Mike, et al.. (2010). DataONE: Survey of Earth Scientists, To Share or Not to Share Data. AGUFM. 2010.2 indexed citations
15.
Gil, Inigo San, et al.. (2010). Metadata Activities in Biology. Journal of Library Metadata. 10(2-3). 99–118.10 indexed citations
16.
Michener, William K., et al.. (2009). DataONE: Enabling Data-Intensive Biological and Environmental Research through Cyberinfrastructure. AGUFM. 2009.1 indexed citations
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.