Published by: The National Center for Geographic Information and Analysis (NCGIA)
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 711 | 21 | 23 | 7 |
The journal explores disciplines such as Data science, Artificial intelligence, Spatial analysis, Data mining and Information retrieval. Journal of Spatial Information Science addresses concerns in Data science which are intertwined with other disciplines, such as Geospatial analysis, Visual analytics, Geographic information system, Semantics and Big data. The Geographic information system works, particularly on GIS and public health are tackled in the journal.
Journal of Spatial Information Science holds forums on Artificial intelligence that merges themes from other disciplines such as Context (language use), Human–computer interaction, Computer vision, Machine learning and Pattern recognition. The journal connects research in Machine learning with the related topic of Similarity (psychology). The work on Pattern recognition addressed in Journal of Spatial Information Science expands to the thematically related Feature (computer vision).
The study on Information retrieval presented is investigated in conjunction with research in Metadata.
The most cited papers facilitate discussions on Data mining, Term (time), Geographic information retrieval, Information retrieval and Metadata. The journal publications tackle studies in Preference learning and the interrelated subject of Context (language use) to gain insights into Geographic information retrieval. While Metadata is the focus of the published papers, it also provides insights into the studies of Semantics, User-generated content and Toponymy.
The objective of Journal of Spatial Information Science is to combine knowledge in the areas of Cognitive science, Deconstruction (building), Question answering, Sociology and Spatial cognition. Cognitive science research discussed connects with the study of Natural language understanding.
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 Journal of Spatial Information Science (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 Journal of Spatial Information Science (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, 25.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 66.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 33.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 0.00% 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.
While the Journal of Spatial Information Science provides a wealth of knowledge for individuals interested in data science, artificial intelligence, spatial analysis and more, it's important to consider the real-world application of such disciplines. These can open doors to various career paths, particularly in education. One career that combines the love for spatial sciences, problem-solving, and the desire to educate is being a middle school math teacher. With a focus on concepts such as geometry and spatial awareness, understanding spatial information science principles could offer a unique teaching perspective and enhance the classroom's learning experiences. For instance, in Michigan, becoming a middle school math teacher requires specific steps. These include completing a bachelor's degree, undertaking a teacher preparation program, passing Michigan Test for Teacher Certification, and applying for certification. Further details on how to embark upon this rewarding career path can be found here. Pursuing such a path allows you to apply spatial information science in an impactful way, contributing to the future generation's education. Remember, the knowledge and insights gained from reading the Journal of Spatial Information Science are not only for research purposes but can be used to inspire and educate others. So, why not channel your passion for spatial sciences into a meaningful teaching career? Remember, the knowledge and insights available to you are not just for paper writing or research purposes. They can be used in real-world applications, providing you with varied and meaningful career paths.
Chris Brunsdon;Alexis J. Comber
(2020)Yu Liu;Yihong Yuan;Fan Zhang
(2020)Natalia V. Andrienko;Gennady L. Andrienko
(2020)Mohammad Masoud Rahimi;Elham Naghizade;Mark Stevenson;Stephan Winter
(2020)Martin Raubal
(2020)Stephan Winter
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