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ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
Data sources: ZENODO
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[SZESLR] Semi-automated Systematic Literature Review (SLR) Design and P-graph (Process Graph Theory) SLR Database

Authors: Tóth, Árpád; Suta, Alex; Pimentel, Jean; Argoti, Andres;

[SZESLR] Semi-automated Systematic Literature Review (SLR) Design and P-graph (Process Graph Theory) SLR Database

Abstract

(c) Széchenyi István University and Artificial Intelligence National Laboratory (MILAB) A proposed semi-automated Systematic Literature Review (SLR) design has been deployed to conduct an exhaustive literature review on contributions concerning applications of the P-graph framework as a case study. The P-graph framework (https://p-graph.org) was initially conceived for solving problems related to the synthesis of chemical processes; in particular, the framework has been useful for developing sustainable and resilient systems. The current contribution includes the P-graph SLR database itself, and additionally, the Python scripts used to generate such results. The case study has been selected in view of the authors’ familiarity with the P-graph framework, and because they maintain a manually-collected database of works on the subject. The contributions concerning the framework are easily distinguishable from others involving similar methodologies. It was observed that the implementation of the proposed SLR design extended prior review papers on the P-graph framework and provided additional information on authors and institutions devoted to research on this subject. Generally, it is expected that the dataset will assist researchers, scholars, and practitioners concerned with industrial sustainability in streamlining their literature reviews, thus accelerating the acquisition of pertinent publications that could advance and enrich their own research works on such a subject. Moreover, it is expected that, with proper adaptation, the proposed semi-automated SLR design can be applied to conduct literature reviews in other scientific fields whose results can be validated against existing reviews when available. The normalized P-graph database hereby presented thus can be used as a source of validated information for researchers. The P-graph database was uploaded in various file formats that support database management software (e.g. Zotero .RIS) as well as an "EasyHandle" MS Office (.XLSX) file.

Related Organizations
Keywords

Systematic Literature Review, SLR, Database, P-graph, Sustainability, Automated search

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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