| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1007 | 7 | 8 | 3 |
Data Science Journal primarily tackles World Wide Web, Data science, Knowledge management, Metadata and Data management. The study on World Wide Web presented in Data Science Journal intersects with the topics under Database. Data science research presented in Data Science Journal encompasses a variety of subjects, including Context (language use) and Big data.
The journal investigates Metadata research which frequently intersects with Information retrieval. Data Science Journal connects research in Data management with the related topic of Public relations.
The journal articles generally zeroe in on subjects such as Data science, World Wide Web, Big data, Data quality and Data mining. The journal publications hold forums on Data science that merge themes from other disciplines such as Data access, Science policy, Data management and Notation. The journal papers focus on World Wide Web but the discussions also offer insight into other areas such as e-Science, Spatial data infrastructure and Service (systems architecture).
The journal investigates studies in Knowledge management, Data science, Metadata, Open science and Data management. The journal explores topics in Knowledge management which can be helpful for research in disciplines like Citizen science, Task (project management), Open research and RDM. Research in Earth observation and the interrelating topic of Environmental data, Data cube and Spatial data infrastructure were among the subjects of interest in the Data science studies discussed in Data Science Journal.
The Metadata research discussed is included in the broader subject of World Wide Web. While work presented in it provided substantial information on Open science, it also covered topics in Train the trainer, Training (civil) and Interoperability. The journal facilitates discussions on Data management that incorporate concepts from other fields like Open data, Reuse, Certification and Process management.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Data Science Journal (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Data Science Journal (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 9.68% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.29% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.71% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 3.57% of all publications and 71.43% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Aspiring contributors to the Data Science Journal need to have a solid understanding of Data Science and the topics regularly featured in the journal. Strong research skills are also necessary, as are analytical abilities to understand and convey complex scientific concepts effectively. It's equally important to possess excellent written communication skills, and the ability to meet publication deadlines.
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Lastly, being proactive in staying updated with emerging trends & developments within data science will serve well. Remember, a successful contributor to the Data Science Journal doesn't just need technical know-how or analytical skills, but also a constant curiosity and the drive to disseminate knowledge.
Nikolas Popper;Melanie Zechmeister;Dominik Brunmeir;Claire Rippinger
(2021)Inna Kouper;Lois Ann Scheidt;Beth A. Plale
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