This map shows the geographic impact of Sara Graves'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 Sara Graves with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Graves more than expected).
This network shows the impact of papers produced by Sara Graves. 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 Sara Graves. The network helps show where Sara Graves may publish in the future.
Co-authorship network of co-authors of Sara Graves
This figure shows the co-authorship network connecting the top 25 collaborators of Sara Graves.
A scholar is included among the top collaborators of Sara Graves 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 Sara Graves. Sara Graves is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wu, Yuling, et al.. (2020). Exploring storm morphology, dynamics and lightning characteristics during the lifecycle of a multicell cluster in a field campaign using a 3D visualization tool.1 indexed citations
4.
Kerkez, Branko, et al.. (2016). Using Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS) in a range of geoscience applications. AGU Fall Meeting Abstracts. 2016.2 indexed citations
Plale, Beth, et al.. (2011). Key Provenance of Earth Science Observational Data Products. AGU Fall Meeting Abstracts. 2011.1 indexed citations
8.
Blakeslee, Richard J., et al.. (2009). A Ten Year Record of Space Based Lightning Measurements. AGUFM. 2009.2 indexed citations
9.
Berendes, Todd, et al.. (2009). Spyglass: A System for Ontology Based Document Retrieval and Visualization.. The Florida AI Research Society.1 indexed citations
10.
Irwin, Daniel, et al.. (2008). SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica. AGUSM. 2008.1 indexed citations
Berendes, Todd, et al.. (2007). Efficient Parallel Computation of Inverse Document Frequency Features for Text Mining.. 273–278.2 indexed citations
13.
Graves, Sara, et al.. (2006). Realizing NASA's Goal of Societal Benefits From Earth Observations in Mesoamerica Through the SERVIR Project. AGUFM. 2006.1 indexed citations
14.
Ramachandran, Rahul, et al.. (2006). Noesis: Ontology based Scoped Search Engine and Resource Aggregator for Atmospheric Science. AGU Fall Meeting Abstracts. 2006.1 indexed citations
Graves, Sara, et al.. (2005). Visualizing Earth Science Data for Environmental Monitoring and Decision Support in Mesoamerica: The SERVIR Project. AGUSM. 2005.1 indexed citations
Ramachandran, Rahul, et al.. (2002). An Interoperable Framework for Mining and Analysis of Space Science Data (F-MASS). AGUFM. 2002.1 indexed citations
19.
Alshayeb, Mohammad, Wei Li, & Sara Graves. (2001). An Empirical Study of Refactoring, New Design, and Error-Fix Efforts in Extreme Programming. 323–325.5 indexed citations
20.
Hinke, Thomas H., et al.. (1997). Target-independent mining for scientific data: capturing transients and trends for phenomena mining. Knowledge Discovery and Data Mining. 187–190.8 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.