## 6 Conclusions and Future Work  
Undertaking systematic reviews is an essential task before starting any research activity. Researchers need to perform a preliminary study of the literature in order to know the current state-of-the-art in a specific research topic. Manually performing this task is very time-consuming for a user. For this reason, several tools have been developed to support systematic reviews. CloudSERA is a cloud-based systematic review tool focused on the realization of systematic literature reviews within the domain of Computer Science. In this work, we have carried out an analysis aimed at gathering the essential evidence synthesis features to provide for a more complete evidence synthesis process in a general-purpose systematic review tool. We have defined a framework that incorporates these features to evaluate and compare existing tools in other domains. With the aim of evaluating the framework and feeding it with more relevant features, an expert survey was carried out. That study has provided us with valuable insights to help improve the CloudSERA tool in supporting the complete set of evidence synthesis functionalities. Moreover, after evaluating existing tools that perform SR processes, we conclude that none of them incorporate all the necessary functionalities for domain experts. For this reason, enhancing CloudSERA by integrating these functionalities can be a promising and viable option.  
We plan to extend CloudSERA with an On-Line Analytical Processing (OLAP) viewer to carry out multi-dimensional analysis easily. In addition, data mining algorithms will be explored and included to discover and cluster data extracted from the primary studies. Additionally, we will incorporate a workflow engine to orchestrate the execution of the tasks to complete an SR process. Finally, we also plan to conduct a heuristic evaluation with the next CloudSERA version using potential end-users from different knowledge areas to measure usability attributes such as learnability, efficiency and user satisfaction.  
Conceptualization, I.R.-R.; methodology, T.P. and J.M.D.; validation, M.J.C. and A.T.; formal analysis, T.P. and J.M.M.; investigation, T.P.; data curation, T.P.; writing--original draft preparation, T.P. and I.R.-R.; writing--review and editing, J.M.D. and A.T.; visualization, J.M.M.; supervision, I.R.-R. and J.M.D.; project administration, J.M.D.; funding acquisition, J.M.D. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Spanish Research Agency (Agencia Estatal de Investigacion) with ERDF funds grant number TIN2017-85797-R (VISAIGLE project). The research stay of [PERSON] in the SFU was funded by Erasmus+ KA107 grant number 2017-1-E501-KA107-037422. The APC was funded by the VISAIGLE project.  
The data used in this paper are available online: the experts' survey and consent form [34]; consent revocation form [35]; and data collection and analysis spreadsheet [36].  
The authors acknowledge the work of [PERSON] in the software implementation of the first version of CloudSERA tool.  
The authors declare that they have no conflict of interests.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ES & Evidence Synthesis \\ SR & Systematic Review \\ RQ & Research Question \\ SMS & Systematic Mapping Study \\ SLR & Systematic Literature Review \\ OLAP & On-Line Analytical Processing \\ \end{tabular}