Haak Laurel

3.2k citations
47 papers · 2.0k indexed · 1 hit paper · h-index 15

Impact in

Papers in

Haak Laurel

39 papers receiving 1.9k citations

Hit Papers

Race, Ethnicity, and NIH Research Awards 2011 · 702 citations
7022011202620162021200400600

Peers

Haak Laurel
Comparison fields: 5 of 168
  • Developmental Neuroscience 256
  • Gender Studies 479
  • Statistics, Probability and Uncertainty 222
  • Cellular and Molecular Neuroscience 479
  • Physiology 95
Replace B. Ian Hutchins with:
B. Ian Hutchins United States
Pamela Kent Australia
Philip R. Lee United States
Ian Pearce United Kingdom
William A. Owens United States
Lesley A. Schimanski United States
Elizabeth Hackett United States
David C. Perry United States
Maria Hägglund Sweden
Stefano Ruggieri Italy
Haak Laurel relative to B. Ian Hutchins United States B. Ian Hutchins's profile →
Citations per field
00.5×7.9×
B. Ian Hutchins · 1×
Citations per year

Countries citing papers authored by Haak Laurel

Since Specialization
Citations

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

Fields of papers citing papers by Haak Laurel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20232
3 20231
4 20212
5 20190
6 20170
7 20170
8 20162
9 20154
10 20145
11 20138
12 2012174
13 201262
14 20069
15 20029
16 2002436
17 200025
18 2000177
19 199932
20 199115

About Haak Laurel

Haak Laurel is a scholar working on Information Systems and Management, Information Systems, Management Science and Operations Research, Statistics, Probability and Uncertainty and Cellular and Molecular Neuroscience, having authored 47 papers that have together received 2.0k indexed citations. Recurring topics across this work include Research Data Management Practices (15 papers), Scientific Computing and Data Management (14 papers), Data Quality and Management (9 papers), Neuroscience and Neuropharmacology Research (7 papers), scientometrics and bibliometrics research (5 papers), Health and Medical Research Impacts (4 papers), Semantic Web and Ontologies (4 papers) and Diversity and Career in Medicine (3 papers). The work is most often cited by research in Developmental Neuroscience (256 citations), Gender Studies (479 citations), Statistics, Probability and Uncertainty (222 citations), Cellular and Molecular Neuroscience (479 citations) and Physiology (95 citations). Haak Laurel has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Donna K. Ginther, Raynard Kington, Walter T. Schaffer, Joshua D. Schnell, R. Douglas Fields, Beth Stevens, Vittorio Gallo, James T. Russell, Laura Paglione and Martin Fenner. Their work appears in journals such as Science, Journal of Neuroscience, Journal of the History of the Neurosciences, Learned Publishing and Insights the UKSG journal.

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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