Craig Sayers

27 papers receiving 467 citations

Peers

Craig Sayers
Comparison fields: 5 of 53
  • Computer Networks and Communications 215
  • Artificial Intelligence 276
  • Signal Processing 81
  • Information Systems 129
  • Human-Computer Interaction 30
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Kazuhiko Kato Japan
Douglas L. Vail United States
A. Smailagic United States
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Béat Hirsbrunner Switzerland
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Citations per year

Countries citing papers authored by Craig Sayers

Since Specialization
Citations

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

Fields of papers citing papers by Craig Sayers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Craig Sayers, 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 Craig Sayers Line = papers co-authored together Craig Sayers links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Efficient RDF Storage and Retrieval in Jena2
2003239
2 199969
3 199455
4 199825
5
Computing the digest of an RDF graph
200421
6
Node-centric RDF Graph Visualization
200415
7
Application-Specific Schema Design for Storing Large RDF Datasets.
200312
8 200212
9
Supporting Scalable, Persistent Semantic Web Applications.
20037
10 19936
11
Operator control of telerobotic systems for real world intervention
19956
12
Creating Context-Aware Software Agents
20015
13 20065
14 20055
15
An ontology for publishing and scheduling events and the lessons learned in developing it.
20024
16 20024
17 19944
18
A continuously adaptable artificial neural network
19894
19
The case for generating URIs by hashing RDF content
20023
20
A pragmatic approach to storing and distributing RDF in context using Snippets
20033

About Craig Sayers

Craig Sayers is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Mechanical Engineering and Control and Systems Engineering, having authored 30 papers that have together received 516 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (9 papers), Teleoperation and Haptic Systems (8 papers), Service-Oriented Architecture and Web Services (5 papers), Advanced Database Systems and Queries (5 papers), Underwater Vehicles and Communication Systems (4 papers), Digital Rights Management and Security (3 papers), Peer-to-Peer Network Technologies (3 papers) and Advanced Data Storage Technologies (3 papers). The work is most often cited by research in Computer Networks and Communications (215 citations), Artificial Intelligence (276 citations), Signal Processing (81 citations), Information Systems (129 citations) and Human-Computer Interaction (30 citations). Craig Sayers has collaborated with scholars based in United States and New Zealand. Frequent co-authors include Kevin Wilkinson, Harumi Kuno, Dave Reynolds, Richard P. Paul, Alan H. Karp, D. Yoerger, Louis L. Whitcomb, Luping Ding, Rohan Paul and George Coghill. Their work appears in journals such as Distributed and Parallel Databases, Industrial Robot the international journal of robotics research and application, Journal of Biosciences, PRESENCE Virtual and Augmented Reality and IEEE Journal of Oceanic Engineering.

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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