Analysing Scholarly Communication Metadata of Computer Science Events
Analysing Scholarly Communication Metadata of Computer Science Events | |
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Analysing Scholarly Communication Metadata of Computer Science Events
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Bibliographical Metadata | |
Keywords: | Scientific Events, Scholarly Communication, Semantic Publishing, Metadata Analysis |
Year: | 2017 |
Authors: | Said Fathalla, Sahar Vahdati, Christoph Lange, Sören Auer |
Venue | TPDL |
Content Metadata | |
Problem: | No data available now. |
Approach: | No data available now. |
Implementation: | No data available now. |
Evaluation: | No data available now. |
Contents
Abstract
Over the past 30 years, we have observed the impact of the ubiquitous availability of the Internet, email, and web-based services on scholarly communication. The preparation of manuscripts as well as the organization of conferences, from submission to peer review to publication, have become considerably easier and e�cient. A key question now is what were the measurable effects on scholarly communication in computer science? Of particular interest are the following questions: Did the number of submissions to conferences increase? How did the selection processes change? Is there a proliferation of publications? We shed light on some of these questions by analyzing comprehensive scholarly communication metadata from a large number of computer science conferences of the last 30 years. Our transferable analysis methodology is based on descriptive statistics analysis as well as exploratory data analysis and uses crowd-sourced, semantically represented scholarly communication metadata from OpenResearch.org.
Conclusion
In summary, we made the following observations: With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. In summary, we made the following observations: With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. Geographical distribution is not generally relevant; some good conferences take place in the same location; others cycle between continents. Good conferences always take place around the same time of the year. This might mean that the community got used to them being important events. Some topics have attracted increasing interest recently e.g., database topics thanks to the `big data' trend. This might be confirmed by further investigations into more recent, emerging events in such fields.
Future work
In further research, we aim to expand the analysis to other fields of science and to smaller events. Also, it is interesting to assess the impact of digitisation with regard to further scholarly communication means, such as journals (which are more important in fields other than computer science), workshops, funding calls and proposal applications as well as awards. Although large parts of our analysis methodology are already automated, we plan to further optimise the process so that analysis can be almost instantly generated from the OpenResearch data basis.
Approach
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Implementations
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Research Problem
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Evaluation
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Access API | No data available now. + |
Event in series | TPDL + |
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Has DataCatalouge | {{{Catalogue}}} + |
Has Description | No data available now. + |
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Has Evaluation | No data available now. + |
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Has GUI | No + |
Has Hypothesis | No data available now. + |
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Has InfoRepresentation | No data available now. + |
Has Limitations | No data available now. + |
Has NegativeAspects | No data available now. + |
Has PositiveAspects | No data available now. + |
Has Requirements | No data available now. + |
Has Results | No data available now. + |
Has Subproblem | No data available now. + |
Has Version | No data available now. + |
Has abstract | Over the past 30 years, we have observed t … Over the past 30 years, we have observed the impact of the
munication
metadata from OpenResearch.org. +ubiquitous availability of the Internet, email, and web-based services on scholarly communication. The preparation of manuscripts as well as the organization of conferences, from submission to peer review to publication, have become considerably easier and e�cient. A key question now is what were the measurable effects on scholarly communication in computer science? Of particular interest are the following questions: Did the number of submissions to conferences increase? How did the selection processes change? Is there a proliferation of publications? We shed light on some of these questions by analyzing comprehensive scholarly communication metadata from a large number of computer science conferences of the last 30 years. Our transferable analysis methodology is based on descriptive statistics analysis as well as exploratory data analysis and uses crowd-sourced, semantically represented scholarly communication metadata from OpenResearch.org. |
Has approach | No data available now. + |
Has authors | Said Fathalla +, Sahar Vahdati +, Christoph Lange + and Sören Auer + |
Has conclusion | In summary, we made the following observat … In summary, we made the following observations:
re recent, emerging events in such fields. +With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. In summary, we made the following observations: With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. Geographical distribution is not generally relevant; some good conferences take place in the same location; others cycle between continents. Good conferences always take place around the same time of the year. This might mean that the community got used to them being important events. Some topics have attracted increasing interest recently e.g., database topics thanks to the `big data' trend. This might be confirmed by further investigations into more recent, emerging events in such fields. |
Has future work | In further research, we aim to expand the … In further research, we aim to expand the analysis to other fields of science
enerated from the OpenResearch data basis. +and to smaller events. Also, it is interesting to assess the impact of digitisation with regard to further scholarly communication means, such as journals (which are more important in fields other than computer science), workshops, funding calls and proposal applications as well as awards. Although large parts of our analysis methodology are already automated, we plan to further optimise the process so that analysis can be almost instantly generated from the OpenResearch data basis. |
Has keywords | Scientific Events, Scholarly Communication, Semantic Publishing, Metadata Analysis + |
Has motivation | No data available now. + |
Has platform | No data available now. + |
Has problem | No data available now. + |
Has relatedProblem | No data available now. + |
Has vendor | No data available now. + |
Has year | 2017 + |
ImplementedIn ProgLang | No data available now. + |
Proposes Algorithm | No data available now. + |
RunsOn OS | No data available now. + |
Title | Analysing Scholarly Communication Metadata of Computer Science Events + |
Uses Framework | No data available now. + |
Uses Methodology | No data available now. + |
Uses Toolbox | No data available now. + |