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.
A survey of data provenance in e-science
2005699 citationsYogesh Simmhan, Beth Plale et al.profile →
The Open Provenance Model core specification (v1.1)
2010429 citationsJames D. Myers, Beth Plale et al.profile →
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 Beth Plale'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 Beth Plale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beth Plale more than expected).
This network shows the impact of papers produced by Beth Plale. 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 Beth Plale. The network helps show where Beth Plale may publish in the future.
Co-authorship network of co-authors of Beth Plale
This figure shows the co-authorship network connecting the top 25 collaborators of Beth Plale.
A scholar is included among the top collaborators of Beth Plale 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 Beth Plale. Beth Plale is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Caylor, K. K., Tom Evans, Lyndon Estes, et al.. (2014). Impacts of Agricultural Decision Making and Adaptive Management on Food Security in Africa. AGUFM. 2014.1 indexed citations
Plale, Beth, et al.. (2012). Active and Social Data Curation: Reinventing the Business of Community-scale Lifecycle Data Management. AGUFM. 2012.1 indexed citations
10.
Miller, Therese, et al.. (2012). 2011 annual report on training, education, and outreach activities of the Indiana University Pervasive Technology Institute and affiliated organizations. IUScholarWorks (Indiana University).1 indexed citations
11.
Simmhan, Yogesh & Beth Plale. (2011). Using Provenance for Personalized Quality Ranking of Scientific Datasets.. 18. 180–195.7 indexed citations
12.
Plale, Beth, et al.. (2011). Key Provenance of Earth Science Observational Data Products. AGU Fall Meeting Abstracts. 2011.1 indexed citations
13.
Katz, Daniel S., S. Callaghan, Robert P. Harkness, et al.. (2010). Science on the TeraGrid. Computational Methods in Science and Technology. Special Issue(1). 81–97.3 indexed citations
Siek, Katie A., et al.. (2006). Breaking the Geek Myth: Addressing Young Women's Misperceptions about Technology Careers.. Learning and leading with technology. 33(7). 19–22.8 indexed citations
16.
Liu, Ying & Beth Plale. (2006). Multi-model Based Optimization for Stream Query Processing.. Software Engineering and Knowledge Engineering. 150–155.4 indexed citations
17.
Liu, Ying & Beth Plale. (2006). Query Optimization for Distributed Data Streams.. 259–266.2 indexed citations
18.
Plale, Beth, Peter A. Dinda, & Gregor von Laszewski. (2002). Key Concepts and Services of a Grid Information Service. 55(9). 614–22.25 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.