Difference between revisions of "Submissions:2021/WikiLetters Systematic Review"
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{{WCNA 2021 Session Submission |
{{WCNA 2021 Session Submission |
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|theme=Tech & Tools |
|theme=Tech & Tools |
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|type=Presentation |
|type=Presentation |
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| − | |abstract=A "'''[[:en:literature review|literature review]]'''" is the common research practice of |
+ | |abstract=A "'''[[:en:literature review|literature review]]'''" is the common research practice of surveying and summarizing research publications on a particular topic. When researchers conduct a literature review in a way that is reproducible and quantitative, then it becomes a "'''[[:en:systematic review|systematic review]]'''". '''Here we share the WikiLetters Method-Tool (MT)''' as an asset for generating systematic reviews using '''[[:en:wikipedia|Wikipedia]]''' platform content and '''[[:en:data science|data science]]''' technology to quickly identify and profile sets of '''[[:en:scientific journals|scientific journals]]''' with great '''[[:en:reproducibility|reproducibility]]'''. |
| − | To operate this MT, the researcher gives the tool |
+ | To operate this MT, the researcher gives the tool between 100-1000 '''[[:en:scientific journals|scholarly publications]]''' which they have identified as being possible candidates for inclusion in the systematic review required knowledge of a subject. The MT then clusters the papers into two groups: those which are the most likely to discuss the topic enough to merit inclusion in the review, and those which are most likely to diverge from scope. Furthermore, this tool provide means of transparency so that any other researcher can examine the selection algorithm which this tool creates. |
| − | This MT imagines the Wikipedia platform as a starting point for scholarly literature review in any field. It builds upon the '''[[: |
+ | This MT imagines the Wikipedia platform as a starting point for scholarly literature review in any field. It builds upon the '''[[:meta:WikiCite|WikiCite]]''' project, which is the '''[[:en:wikidata|Wikidata]]''' community effort to open metadata from Scholarly literature, by matching metadata from that dataset with contemporary algorithms for analysis and visualization. |
| − | While other tools for aiding systematic review exist, benefits of this one include the following: it is free |
+ | While other tools for aiding systematic review exist, benefits of this one include the following: it is free and open; it is usable by people who are new to systematic review; it is reproducible and gives the author documentation of the selection method; it advances the activism and consumer rights protection of the existing WikiCite project; it develops the Wikipedia platform as a center serious scholarly research; and aside from scholarly use, it enables Wikipedia editors to use the systematic review ranking process to identify the best papers to cite for developing any Wikipedia article which is the subject of academic publication. Furthermore, Wiki-editors can use this MT to append recent research into existing systematic reviews and turning those into a living systematic review for use either in Wikipedia or beyond. |
|academic=Yes |
|academic=Yes |
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|presented=no |
|presented=no |
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|present-other=yes |
|present-other=yes |
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| − | |status= |
+ | |status=Accepted |
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Latest revision as of 00:09, 28 October 2022
This submission has been accepted for WikiConference North America 2021.
Title:
- WikiLetters Systematic Review
Theme:
- Tech & Tools
Type of session:
- Presentation
Abstract:
A "literature review" is the common research practice of surveying and summarizing research publications on a particular topic. When researchers conduct a literature review in a way that is reproducible and quantitative, then it becomes a "systematic review". Here we share the WikiLetters Method-Tool (MT) as an asset for generating systematic reviews using Wikipedia platform content and data science technology to quickly identify and profile sets of scientific journals with great reproducibility.
To operate this MT, the researcher gives the tool between 100-1000 scholarly publications which they have identified as being possible candidates for inclusion in the systematic review required knowledge of a subject. The MT then clusters the papers into two groups: those which are the most likely to discuss the topic enough to merit inclusion in the review, and those which are most likely to diverge from scope. Furthermore, this tool provide means of transparency so that any other researcher can examine the selection algorithm which this tool creates.
This MT imagines the Wikipedia platform as a starting point for scholarly literature review in any field. It builds upon the WikiCite project, which is the Wikidata community effort to open metadata from Scholarly literature, by matching metadata from that dataset with contemporary algorithms for analysis and visualization.
While other tools for aiding systematic review exist, benefits of this one include the following: it is free and open; it is usable by people who are new to systematic review; it is reproducible and gives the author documentation of the selection method; it advances the activism and consumer rights protection of the existing WikiCite project; it develops the Wikipedia platform as a center serious scholarly research; and aside from scholarly use, it enables Wikipedia editors to use the systematic review ranking process to identify the best papers to cite for developing any Wikipedia article which is the subject of academic publication. Furthermore, Wiki-editors can use this MT to append recent research into existing systematic reviews and turning those into a living systematic review for use either in Wikipedia or beyond.
Academic Peer Review option:
- Yes
Author name:
E-mail address:
- fernando_andutta
yahoo.com.br; driemeieusp.br; joharariusp.br; marcoslopesusp.br; daniel.mietchenibmt.fraunhofer.de; rasberryvirginia.edu
Wikimedia username:
- bluerasberry
Affiliated organization(s):
- Polytechnic Institute, Oceanographic Institute, and Department of Linguistics at the University of Sao Paulo; School of Data Science, University of Virginia
Estimated time:
- 25 minutes
Special requests:
Have you presented on this topic previously? If yes, where/when?:
- no
If your submission is not accepted, would you be open to presenting your topic in another part of the program? (e.g. lightning talk or unconference session)
- yes