Data Analysis Tools

Research tools are used for data analysis, enabling researchers to make informed decisions. 

• Atlas.ti 23 is computer-assisted qualitative data analysis software that facilitates qualitative research analysis.
• IBM SPSS & AMOS is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytics.
• MATLAB analyse and designs the systems and products transforming our world
• OpenRefine is a powerful, free, open-source tool for working with messy data: cleaning it, transforming it from one format into another, and extending it with web services and external data.
• R  is open-source software for data manipulation, calculation, and graphical display.
• SAS (Statistical Analysis System) is a software suite developed by the SAS Institute for advanced analytics, multivariate analyses, and business intelligence.
• Statistica provides the most comprehensive array of data analysis, data management, visualisation, and mining procedures. Its techniques include the widest selection of predictive modelling, clustering, classification, and exploratory techniques in one software platform

For research analytics, bibliometrics and scholarly communication, particularly useful tools include:

• SciVal - Research performance and bibliometric analysis 
• Scopus - Citation, author, source and research-output analysis 
• Web of Science - Citation and research-impact analysis 
• VOSviewer - Bibliometric networks and research mapping 
• Bibliometrix/Biblioshiny - Bibliometric analysis using R 
• OpenAlex - Open scholarly metadata and bibliometric analysis, Ideal for discovering, analysing, and integrating academic data.
• Dimensions - Research, citation and funding analytics 
• Altmetric Explorer - Alternative research-impact/attention analysis