Towards Evidence-Based Understanding of Electronic Data Sources

Lianping Chen, Muhammad Ali Babar, He Zhang

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Identifying relevant papers from various Electronic Data Sources (EDS) is one of the key activities of conducting these kinds of studies. Hence, the selection of EDS for searching the potentially relevant papers is an important decision, which can affect a study’s coverage of relevant papers. Researchers usually select EDS mainly based on personal knowledge, experience, and preferences and/or recommendations by other researchers. We believe that building an evidence-based understanding of EDS can enable researchers to make more informed decisions about the selection of EDS. This paper reports our initial effort towards this end. We propose an initial set of metrics for characterizing the EDS from the perspective of the needs of secondary studies. We explain the usage and benefits of the proposed metrics using the data gathered from two secondary studies. We also tried to synthesize the data from the two studies and that from literature to provide initial evidence-based heuristics for EDS selection.
Original languageEnglish
Title of host publication14th International Conference on Evaluation and Assessment in Software Engineering (EASE)
PublisherBritish Computer Society
Publication date2010
Publication statusPublished - 2010
Event14th International Conference on Evaluation and Assessment in Software Engineering (EASE) - Keele, United Kingdom
Duration: 12 Apr 201013 Apr 2010
Conference number: 14th
http://www.scm.keele.ac.uk/ease/ease2010.html

Conference

Conference14th International Conference on Evaluation and Assessment in Software Engineering (EASE)
Number14th
Country/TerritoryUnited Kingdom
CityKeele
Period12/04/201013/04/2010
Internet address

Cite this