Robert Binna

652 citations
6 papers · 455 · h-index 5

Impact in

  • Archeology top 2%
    • Forensic Anthropology and Bioarchaeology Studies
  • Genetics top 10%
    • Forensic and Genetic Research
    • Genetic diversity and population structure
    • Yersinia bacterium, plague, ectoparasites research

Papers in

Robert Binna

6 papers receiving 452 citations

Peers

Robert Binna
Comparison fields: 5 of 80
  • Archeology 121
  • Genetics 263
  • Paleontology 47
  • Clinical Biochemistry 31
  • Hardware and Architecture 26
Replace H-J Bandelt with:
H-J Bandelt Germany
Simone Rubinacci Switzerland
Simon Hickinbotham United Kingdom
Manuel García‐Magariños Spain
Lawrence A. Presley United States
S.S. Kind United Kingdom
Christine S. Flaxman United Kingdom
Anthony J. Onorato United States
James Hester United States
Elsa G. Guillot New Zealand
Robert Binna relative to H-J Bandelt Germany H-J Bandelt's profile →
Citations per field
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Citations per year

Countries citing papers authored by Robert Binna

Since Specialization
Citations

This map shows the geographic impact of Robert Binna'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 Robert Binna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Binna more than expected).

Fields of papers citing papers by Robert Binna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Binna. 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 Robert Binna. The network helps show where Robert Binna may publish in the future.

Co-authors

The 10 scholars most cited alongside Robert Binna, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robert Binna Line = papers co-authored together Robert Binna links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 2010376
2 201859
3
SpiderStore: Exploiting Main Memory for Efficient RDF Graph Representation and Fast Querying
20109
4
SpiderStore: A Native Main Memory Approach for Graph Storage
20116
5 20224
6
Fast and space-efficient indexing for main-memory database systems on modern hardware
20201

About Robert Binna

Robert Binna is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology and Information Systems, having authored 6 papers that have together received 455 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (5 papers), Graph Theory and Algorithms (2 papers), Semantic Web and Ontologies (2 papers), Advanced Data Storage Technologies (2 papers), Forensic and Genetic Research (1 paper), Parallel Computing and Optimization Techniques (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper) and Data Management and Algorithms (1 paper). The work is most often cited by research in Archeology (121 citations), Genetics (263 citations), Paleontology (47 citations), Clinical Biochemistry (31 citations) and Hardware and Architecture (26 citations). Robert Binna has collaborated with scholars based in Austria and Germany. Frequent co-authors include Günther Specht, Dominic Pacher, Florian Kronenberg, Hansi Weißensteiner, Anita Kloss‐Brandstätter, Sebastian Schönherr, Eva Zangerle, Martin Pichl, Viktor Leis and W. Gässler. Their work appears in journals such as Human Mutation, ACM Transactions on Database Systems and Digital Library of the University of Innsbruck (University of Innsbruck).

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.

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