Daniel Groß
- Information Systems top 5%
- Artificial Intelligence top 10%
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
- Social Psychology
- Co-authors
- Eric YuScott R. VranaBoaz M. Ben‐DavidChariklia TzirakiRonald HübnerMichael DambacherArnon SturmMaría Carmela Annosi
- Topics
- Semantic Web and Ontologies (4 papers)Business Process Modeling and Analysis (2 papers)Information Systems Theories and Implementation (2 papers)
- Partner nations
- CanadaIsraelUnited States
In The Last Decade
Daniel Groß
12 papers receiving 275 citations
Peers
Comparison fields: 5 of 80
- Information Systems 110
- Artificial Intelligence 99
- Experimental and Cognitive Psychology 65
- Cognitive Neuroscience 64
- Social Psychology 38
Countries citing papers authored by Daniel Groß
This map shows the geographic impact of Daniel Groß'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 Groß with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Groß more than expected).
Fields of papers citing papers by Daniel Groß
This network shows the impact of papers produced by Daniel Groß. 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 Groß. The network helps show where Daniel Groß may publish in the future.
Co-authorship network of co-authors of Daniel Groß
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Groß. A scholar is included among the top collaborators of Daniel Groß 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 Daniel Groß. Daniel Groß is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 4 | |
| 3 | 14 | |
| 4 | Know-How Mapping: From i* to ME-maps. | 2 |
| 5 | Towards Know-how Mapping Using Goal Modeling | 1 |
| 6 | 0 | |
| 7 | 10 | |
| 8 | Analyzing Knowledge Transfer in Software Maintenance Organizations using an Agent- and Goal-oriented Analysis Technique - an Experience Report. | 1 |
| 9 | Analyzing Software Process Alignment with Organizational Business Strategies Using an Agent- and Goal-oriented Analysis technique - An Experience Report | 2 |
| 10 | 91 | |
| 11 | 136 | |
| 12 | 3 | |
| 13 | 11 |
About Daniel Groß
Daniel Groß is a scholar working on General Decision Sciences, Management Information Systems and Software, having authored 13 papers that have together received 303 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (4 papers), Business Process Modeling and Analysis (2 papers) and Information Systems Theories and Implementation (2 papers). The work is most often cited by research in Software (33 citations), Experimental and Cognitive Psychology (65 citations) and Information Systems (110 citations). Daniel Groß has collaborated with scholars based in Canada, Israel and United States. Frequent co-authors include Eric Yu, Scott R. Vrana, Boaz M. Ben‐David, Chariklia Tziraki, Ronald Hübner, Michael Dambacher, Arnon Sturm, María Carmela Annosi, Robert E. Vann and Susan Robinson. Their work appears in journals such as Pharmacology Biochemistry and Behavior, Biological Psychology and Journal of Knowledge Management.
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.