Markus Scheidgen

1.2k citations
41 papers · 436 · h-index 10

Impact in

Papers in

    • Service-Oriented Architecture and Web Services 10
    • Software Engineering Research 4
    • Model-Driven Software Engineering Techniques 16

Markus Scheidgen

35 papers receiving 410 citations

Peers

Markus Scheidgen
Comparison fields: 5 of 71
  • Software 169
  • Information Systems and Management 52
  • Information Systems 148
  • Artificial Intelligence 148
  • Management Information Systems 34
Replace Ziyue Yang with:
Ziyue Yang China
Qianxiang Wang China
Felix Fischer Germany
Muhammad Waseem Finland
Chien‐Min Wang Taiwan
Alan R. Simon United States
Saurabh Tiwari India
Anubha Jain India
Weisong Sun China
Markus Scheidgen relative to Ziyue Yang China Ziyue Yang's profile →
Citations per field
00.5×10×17×
Ziyue Yang · 1×
Citations per year

Countries citing papers authored by Markus Scheidgen

Since Specialization
Citations

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

Fields of papers citing papers by Markus Scheidgen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022155
2 200835
3 200730
4 201227
5 201218
6 202216
7 200516
8 202014
9 200713
10 201310
11 20219
12 20129
13 20128
14 20138
15 20127
16 20126
17 20065
18 20165
19 20055
20 20084

About Markus Scheidgen

Markus Scheidgen is a scholar working on Information Systems, Software, Artificial Intelligence, Computer Networks and Communications and Information Systems and Management, having authored 41 papers that have together received 436 indexed citations. Recurring topics across this work include Model-Driven Software Engineering Techniques (16 papers), Service-Oriented Architecture and Web Services (10 papers), Advanced Software Engineering Methodologies (9 papers), Scientific Computing and Data Management (9 papers), Machine Learning in Materials Science (8 papers), Software System Performance and Reliability (7 papers), Business Process Modeling and Analysis (4 papers) and Software Engineering Research (4 papers). The work is most often cited by research in Software (169 citations), Information Systems and Management (52 citations), Information Systems (148 citations), Artificial Intelligence (148 citations) and Management Information Systems (34 citations). Markus Scheidgen has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Joachim Fischer, Anatolij Zubow, Claudia Draxl, Kurt Kremer, Claudia Felser, Christof Wöll, Hans‐Joachim Bungartz, Matthias Scheffler, Tristan Bereau and Mark Greiner. Their work appears in journals such as Lecture notes in computer science, Computer Networks, Nature, npj Computational Materials and Scientific Data.

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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