Daniel Williams

51 papers receiving 858 citations

Peers

Daniel Williams
Comparison fields: 5 of 126
  • Public Administration 184
  • Otorhinolaryngology 69
  • Hardware and Architecture 104
  • Management Information Systems 124
  • Management Science and Operations Research 139
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İsmail Ertürk Türkiye
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Citations per year

Countries citing papers authored by Daniel Williams

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Williams, 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 Daniel Williams Line = papers co-authored together Daniel Williams links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003124
2 1998109
3 2007108
4 200751
5 200246
6 200645
7 200440
8 200438
9 200036
10
Synergistic Challenges in Data-Intensive Science and Exascale Computing: DOE ASCAC Data Subcommittee Report
201326
11 199325
12 200624
13 200221
14 199920
15 201617
16 201516
17
Social and economic issues of the Hayman Fire
200315
18 201114
19 200713
20 201212

About Daniel Williams

Daniel Williams is a scholar working on Public Administration, Hardware and Architecture, General Economics, Econometrics and Finance, Management Science and Operations Research and Library and Information Sciences, having authored 58 papers that have together received 939 indexed citations. Recurring topics across this work include Public Policy and Administration Research (8 papers), Parallel Computing and Optimization Techniques (7 papers), Monetary Policy and Economic Impact (7 papers), Forecasting Techniques and Applications (6 papers), Fiscal Policies and Political Economy (6 papers), Housing Market and Economics (4 papers), Software System Performance and Reliability (4 papers) and Accounting and Organizational Management (4 papers). The work is most often cited by research in Public Administration (184 citations), Otorhinolaryngology (69 citations), Hardware and Architecture (104 citations), Management Information Systems (124 citations) and Management Science and Operations Research (139 citations). Daniel Williams has collaborated with scholars based in United States, South Korea and Türkiye. Frequent co-authors include Don Miller, Jun Huan, Wei Wang, Greg Chen, Jack W. Davidson, Jason D. Hiser, Nat E. Watson, Kathryn M. Greven, John W. Keyes and Bruce R. Childers. Their work appears in journals such as Public Administration Review, International Journal of Forecasting, International Journal of Public Administration, Journal of Public Budgeting Accounting & Financial Management and Public Performance & Management Review.

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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