Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/kpxl/ios/ds/np/RAWu9Hx_V1AD8Yyl1iad-2jIXWX8GkXhWG-4wEV4YaUQc/assertion>. }
Showing items 1 to 27 of
27
with 100 items per page.
- DS-190019 type ResearchPaper assertion.
- author-list _1 0000-0001-6557-3131 assertion.
- author-list__1 _2 0000-0001-6365-6515 assertion.
- author-list__2 _3 0000-0002-2234-0845 assertion.
- author-list__3 _4 0000-0003-0015-1952 assertion.
- DS-190019 isPartOf 2451-8492 assertion.
- 2451-8492 title "Data Science" assertion.
- DS-190019 title "Reducing the effort for systematic reviews in software engineering" assertion.
- 008xxew50 name "Department of Computer Science, Vrije Universiteit Amsterdam, The Netherlands" assertion.
- 0000-0001-6557-3131 name "Francesco Osborne" assertion.
- 05mzfcs16 name "Knowledge Media Institute, The Open University, UK" assertion.
- 01j9p1r26 name "DISIM Department, University of L’Aquila, Italy" assertion.
- 0000-0001-6365-6515 name "Henry Muccini" assertion.
- 0000-0002-2234-0845 name "Patricia Lago" assertion.
- 0000-0003-0015-1952 name "Enrico Motta" assertion.
- DS-190019 abstract "Context: Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, they use a well-defined methodology meant to mitigate the risks of biases and ensure repeatability for later updates. SRs, however, involve significant effort. Goal: The goal of this paper is to introduce a novel methodology that reduces the amount of manual tedious tasks involved in SRs while taking advantage of the value provided by human expertise. Method: Starting from current methodologies for SRs, we replaced the steps of keywording and data extraction with an automatic methodology for generating a domain ontology and classifying the primary studies. This methodology has been applied in the Software Engineering sub-area of Software Architecture and evaluated by human annotators. Results: The result is a novel Expert-Driven Automatic Methodology, EDAM, for assisting researchers in performing SRs. EDAM combines ontology-learning techniques and semantic technologies with the human-in-the-loop. The first (thanks to automation) fosters scalability, objectivity, reproducibility and granularity of the studies; the second allows tailoring to the specific focus of the study at hand and knowledge reuse from domain experts. We evaluated EDAM on the field of Software Architecture against six senior researchers. As a result, we found that the performance of the senior researchers in classifying papers was not statistically significantly different from EDAM. Conclusions: Thanks to automation of the less-creative steps in SRs, our methodology allows researchers to skip the tedious tasks of keywording and manually classifying primary studies, thus freeing effort for the analysis and the discussion." assertion.
- DS-190019 date "2019-08-19" assertion.
- 0000-0001-6557-3131 email "francesco.osborne@open.ac.uk" assertion.
- 0000-0001-6365-6515 email "henry.muccini@univaq.it" assertion.
- 0000-0002-2234-0845 email "p.lago@vu.nl" assertion.
- 0000-0003-0015-1952 email "enrico.motta@open.ac.uk" assertion.
- DS-190019 volume "2" assertion.
- 0000-0001-6557-3131 affiliation 05mzfcs16 assertion.
- 0000-0001-6365-6515 affiliation 01j9p1r26 assertion.
- 0000-0002-2234-0845 affiliation 008xxew50 assertion.
- 0000-0003-0015-1952 affiliation 05mzfcs16 assertion.
- DS-190019 issue "1-2" assertion.