A Comprehensive Framework to Reinforce Evidence Synthesis Features in Cloud-Based Systematic Review Tools
| Autor: | Tatiana Person, Iván Ruiz-Rube, José Miguel Mota, Manuel Jesús Cobo, Alexey Tselykh, Juan Manuel Dodero |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Applied Sciences, Vol 11, Iss 12, p 5527 (2021) |
| Druh dokumentu: | article |
| ISSN: | 11125527 2076-3417 |
| DOI: | 10.3390/app11125527 |
| Popis: | Systematic reviews are powerful methods used to determine the state-of-the-art in a given field from existing studies and literature. They are critical but time-consuming in research and decision making for various disciplines. When conducting a review, a large volume of data is usually generated from relevant studies. Computer-based tools are often used to manage such data and to support the systematic review process. This paper describes a comprehensive analysis to gather the required features of a systematic review tool, in order to support the complete evidence synthesis process. We propose a framework, elaborated by consulting experts in different knowledge areas, to evaluate significant features and thus reinforce existing tool capabilities. The framework will be used to enhance the currently available functionality of CloudSERA, a cloud-based systematic review tool focused on Computer Science, to implement evidence-based systematic review processes in other disciplines. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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