David Hubbard

628 total citations
40 papers, 445 citations indexed

About

David Hubbard is a scholar working on Information Systems, Statistics, Probability and Uncertainty and Neurology. According to data from OpenAlex, David Hubbard has authored 40 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Information Systems, 10 papers in Statistics, Probability and Uncertainty and 8 papers in Neurology. Recurrent topics in David Hubbard's work include scientometrics and bibliometrics research (10 papers), Cerebral Venous Sinus Thrombosis (8 papers) and Open Education and E-Learning (5 papers). David Hubbard is often cited by papers focused on scientometrics and bibliometrics research (10 papers), Cerebral Venous Sinus Thrombosis (8 papers) and Open Education and E-Learning (5 papers). David Hubbard collaborates with scholars based in United States, Canada and Italy. David Hubbard's co-authors include Patrick J. Kinlen, E. Mark Haacke, Wei Feng, David Utriainen, Gabriela Trifan, Jane Stephens, Zahid Latif, Donald Ponec, J. Justin Gooding and Yashwanth Katkuri and has published in prestigious journals such as New England Journal of Medicine, Sensors and Actuators B Chemical and Journal of Vascular and Interventional Radiology.

In The Last Decade

David Hubbard

39 papers receiving 427 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Hubbard United States 12 173 113 85 72 68 40 445
Philip Robinson France 6 23 0.1× 28 0.2× 46 0.5× 3 0.0× 34 0.5× 7 327
Uhn Lee South Korea 11 55 0.3× 3 0.0× 24 0.3× 6 0.1× 17 0.3× 34 465
Asra Al Fauzi Indonesia 10 101 0.6× 5 0.0× 3 0.0× 28 0.4× 74 338
Yang Si China 10 9 0.1× 27 0.2× 56 0.7× 8 0.1× 35 321
Shuiping Huang China 14 23 0.1× 1 0.0× 16 0.2× 4 0.1× 64 0.9× 47 456
Tongtong Xue China 7 10 0.1× 10 0.1× 28 0.3× 1 0.0× 5 0.1× 23 248
Bo Young Kim South Korea 10 32 0.2× 2 0.0× 24 0.3× 4 0.1× 29 0.4× 35 375
Michael Balas Canada 10 28 0.2× 1 0.0× 4 0.0× 37 0.5× 59 452
Shashwat Tripathi United States 11 69 0.4× 6 0.1× 1 0.0× 69 1.0× 34 379
Hirohisa Abe Japan 9 18 0.1× 4 0.0× 43 0.5× 4 0.1× 6 0.1× 28 360

Countries citing papers authored by David Hubbard

Since Specialization
Citations

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

Fields of papers citing papers by David Hubbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Hubbard

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

All Works

20 of 20 papers shown
1.
Hubbard, David, et al.. (2022). Analysis Of Acknowledgments of Libraries in the Journal Literature Using Machine Learning. Proceedings of the Association for Information Science and Technology. 59(1). 709–711. 1 indexed citations
2.
Hubbard, David, et al.. (2022). Retractions in Scopus: An Engineering Journal Articles Investigation. Science & Technology Libraries. 42(3). 353–366. 3 indexed citations
3.
Watts, John, et al.. (2021). Collaborative Data Literacy Education for Research Labs: A Case Study at a Large Research University. Digital Commons - DU (University of Denver). 12(3). 7. 4 indexed citations
4.
Hubbard, David, et al.. (2020). Acknowledgment of Libraries in the Journal Literature: An Exploratory Study. Journal of Data and Information Science. 5(3). 178–186. 7 indexed citations
5.
Hubbard, David. (2020). Analysis Of Asee Eld Conference Proceedings: 2000 2009. 15.177.1–15.177.15. 1 indexed citations
6.
Hubbard, David, et al.. (2019). Representation of Libraries in Funding Acknowledgments.. OakTrust (Texas A&M University Libraries). 2604–2605. 1 indexed citations
7.
Hubbard, David, et al.. (2018). Demonstrating Library Impact Through Acknowledgment: An Examination of Acknowledgments in Theses and Dissertations. The Journal of Academic Librarianship. 44(3). 404–411. 3 indexed citations
8.
Hubbard, David. (2017). Chemical Lecture Demonstrations: An Opportunity for Engagement through Collections, Instruction, and Reference. Science & Technology Libraries. 36(4). 376–389. 3 indexed citations
9.
White, Richard, et al.. (2017). Organising Responses to Organised Environmental Crimes: Collaborative Approaches and Building Capacity. South African Crime Quarterly. 1 indexed citations
10.
Laganà, Maria Marcella, David Utriainen, Wei Feng, et al.. (2014). Cerebrospinal Fluid Flow Dynamics in Multiple Sclerosis Patients through Phase Contrast Magnetic Resonance Imaging. Current Neurovascular Research. 11(4). 349–358. 8 indexed citations
11.
Zivadinov, Robert, Stefano Bastianello, Michael D. Dake, et al.. (2014). Recommendations for Multimodal Noninvasive and Invasive Screening for Detection of Extracranial Venous Abnormalities Indicative of Chronic Cerebrospinal Venous Insufficiency: A Position Statement of the International Society for Neurovascular Disease. Journal of Vascular and Interventional Radiology. 25(11). 1785–1794.e17. 43 indexed citations
12.
Hubbard, David, et al.. (2012). Benchmarking mechanical engineering collections using the WorldCat Collection Analysis tool. Library Collections Acquisitions and Technical Services. 36(3-4). 59–68. 1 indexed citations
13.
Hubbard, David, et al.. (2012). Clinical Improvement after Extracranial Venoplasty in Multiple Sclerosis. Journal of Vascular and Interventional Radiology. 23(10). 1302–1308. 30 indexed citations
14.
Utriainen, David, Wei Feng, Saba Elias, et al.. (2012). Using Magnetic Resonance Imaging as a Means to Study Chronic Cerebral Spinal Venous Insufficiency in Multiple Sclerosis Patients. Techniques in vascular and interventional radiology. 15(2). 101–112. 24 indexed citations
15.
Siskin, Gary P., Ziv J. Haskal, Gordon McLennan, et al.. (2011). Development of a Research Agenda for Evaluation of Interventional Therapies for Chronic Cerebrospinal Venous Insufficiency: Proceedings from a Multidisciplinary Research Consensus Panel. Journal of Vascular and Interventional Radiology. 22(5). 587–593. 11 indexed citations
16.
Hubbard, David. (2010). Corrections in the Chemical Literature: Their Number and Nature. Science & Technology Libraries. 29(1-2). 130–143. 3 indexed citations
17.
Hubbard, David & Lawrence C. Washington. (2009). Kummer generators and lambda invariants. Journal of Number Theory. 130(1). 61–81.
18.
Hubbard, David. (2007). Dihedral side extensions and class groups. Journal of Number Theory. 128(4). 731–737. 1 indexed citations
19.
Hubbard, David. (1992). Forecasting Process at Apple Computer. 11(1). 26–106749. 2 indexed citations
20.
Hurst, J. Willis, et al.. (1958). Precordial Murmurs during Pregnancy and Lactation. New England Journal of Medicine. 259(11). 515–517. 13 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.

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