D. N. Williams

4.5k total citations · 1 hit paper
79 papers, 2.4k citations indexed

About

D. N. Williams is a scholar working on Information Systems and Management, Materials Chemistry and Computer Networks and Communications. According to data from OpenAlex, D. N. Williams has authored 79 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Information Systems and Management, 23 papers in Materials Chemistry and 21 papers in Computer Networks and Communications. Recurrent topics in D. N. Williams's work include Scientific Computing and Data Management (21 papers), Distributed and Parallel Computing Systems (19 papers) and Titanium Alloys Microstructure and Properties (15 papers). D. N. Williams is often cited by papers focused on Scientific Computing and Data Management (21 papers), Distributed and Parallel Computing Systems (19 papers) and Titanium Alloys Microstructure and Properties (15 papers). D. N. Williams collaborates with scholars based in United States, Italy and Germany. D. N. Williams's co-authors include Charles Doutriaux, Karl E. Taylor, Peter J. Gleckler, R. Drach, W. J. Gallagher, Curt Covey, B. P. Fairand, B.A. Wilcox, Gerald L. Potter and James S. Boyle and has published in prestigious journals such as Nature, Journal of Applied Physics and Journal of The Electrochemical Society.

In The Last Decade

D. N. Williams

77 papers receiving 2.3k citations

Hit Papers

align trajectories

What are hit papers?

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.

An Overview of the Results of the Atmospheric Model Intercomparison Project (AMIP I)

1999 678 citations Charles Doutriaux, Gerald L. Potter et al. Bulletin of the American Meteorological Society profile →

Peers

Countries citing papers authored by D. N. Williams

Since Specialization

Citations

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

Fields of papers citing papers by D. N. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. N. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of D. N. Williams. A scholar is included among the top collaborators of D. N. Williams 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 D. N. Williams. D. N. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Requirements for a global data infrastructure in support of CMIP6 2018 ·Geoscientific model development ·V. Balaji, Karl E. Taylor, Martin Juckes, Bryan Lawrence, Paul J. Durack, Michael Lautenschlager, Chris Blanton, L. Cinquini, Sébastien Denvil, Mark Elkington, (unknown), Éric Guilyardi, David Hassell, Slava Kharin, (unknown), S. Nikonov, Aparna Radhakrishnan, Martina Stockhause, Tobias Weigel, D. N. Williams	69
2	ClimateNet: A Machine Learning dataset for Climate Science Research 2017 ·AGU Fall Meeting Abstracts ·(unknown), (unknown), (unknown), (unknown), Karthik Kashinath, (unknown), Samira Ebrahimi Kahou, Tegan Maharaj, Christopher Beckham, (unknown), Michael Wehner, D. N. Williams, Kenneth E. Kunkel, William D. Collins	1
3	Enabling Reanalysis Research Using the Collaborative Reanalysis Technical Environment (CREATE) 2017 ·Bulletin of the American Meteorological Society ·Gerald L. Potter, (unknown), (unknown), Michael G. Bosilovich, Daniel Q. Duffy, Tsengdar Lee, D. N. Williams	16
4	Climate Science's Globally Distributed Infrastructure 2016 ·AGU Fall Meeting Abstracts ·D. N. Williams	1
5	Towards improved and more routine Earth system model evaluation in CMIP 2016 ·Earth System Dynamics ·Veronika Eyring, P. J. Gleckler, Christoph Heinze, Ronald J. Stouffer, Karl E. Taylor, V. Balaji, Éric Guilyardi, Sylvie Joussaume, Stephan Kindermann, Bryan Lawrence, Gerald A. Meehl, Mattia Righi, D. N. Williams	77
6	The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change 2015 ·2015 AGU Fall Meeting ·Sandro Fiore, D. N. Williams, (unknown), (unknown), Giovanni Aloisio	1
7	The Earth System Grid Federation (ESGF): Climate Science Infrastructure for Large-scale Data Management and Dissemination 2015 ·2015 AGU Fall Meeting ·D. N. Williams	1
8	A Global Repository for Planet-Sized Experiments and Observations 2015 ·Bulletin of the American Meteorological Society ·D. N. Williams, V. Balaji, L. Cinquini, Sébastien Denvil, Daniel Q. Duffy, Ben Evans, R. Ferraro, (unknown), Michael Lautenschlager, Claire Trenham	29
9	Ophidia: A full software stack for scientific data analytics 2014 ·Institutional Research Information System (Università degli Studi di Trento) ·Sandro Fiore, (unknown), Donatello Elia, (unknown), D. N. Williams, Ian Foster, Giovanni Aloisio	11
10	The Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT): Data Analysis and Visualization for Geoscience Data 2013 ·Computer ·D. N. Williams, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown)	2
11	UV-CDAT: Analyzing Climate Datasets from a User's Perspective 2013 ·Computing in Science & Engineering ·Emanuele Santos, Jorge Poco, Yaxing Wei, Shishi Liu, (unknown), D. N. Williams, Claudio Silva	23
12	Earth System Grid Center for Enabling Technologies (ESG-CET): A Data Infrastructure for Data-Intensive Climate Research 2011 ·University of North Texas Digital Library (University of North Texas) ·D. N. Williams	2
13	Visualization of uncertainty and ensemble data: Exploration of climate modeling and weather forecast data with integrated ViSUS-CDAT systems 2009 ·Journal of Physics Conference Series ·Kristin Potter, Andrew T. Wilson, Peer‐Timo Bremer, D. N. Williams, Charles Doutriaux, Valerio Pascucci, (unknown)	44
14	A Climate Data Analysis Tool: An Open Software System Approach 2001 ·AGU Spring Meeting Abstracts ·D. N. Williams	2
15	Visualizing wind velocities by advecting cloud textures 1992 ·IEEE Visualization ·Nelson Max, Roger Crawfis, D. N. Williams	46
16	Subcritical crack growth under sustained load 1974 ·Metallurgical Transactions ·D. N. Williams	24
17	The effect of composition on the mechanism of stress-corrosion cracking of titanium alloys in N2O4, and aqueous and hot-salt environments 1971 ·J. D. Boyd, (unknown), W. K. Boyd, Richard Wood, D. N. Williams, R.I. Jaffee	1
18	Relationships between impact and low-strain-rate hydrogen embrittlement of titanium alloys 1960 ·Journal of the Less Common Metals ·D. N. Williams, R.I. Jaffee	11
19	HYDROGEN IN TITANIUM-ALUMINUM ALLOYS 1958 ·Lothar Berger, D. N. Williams, R.I. Jaffee	2
20	A THEORETICAL INVESTIGATION OF THE DEFORMATION TEXTURES OF TITANIUM 1953 ·D. N. Williams, (unknown)	6

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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