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Most of ResearchGate's users are involved in medicine or biology, [10] [12] though it also has participants from engineering, law, computer science, agricultural sciences, and psychology, among others. [10] ResearchGate published an author-level metric in the form of an "RG Score" since 2012. [15] RG score is not a citation impact measure.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business ...
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.
They are also referred to as Internet research, [1] Internet science [2] or iScience, or Web-based methods. [3] Many of these online research methods are related to existing research methodologies but re-invent and re-imagine them in the light of new technologies and conditions associated with the internet. The field is relatively new and evolving.
Mobile data collection or mobile surveys is an increasingly popular method of data collection. Over 50% of surveys today are opened on mobile devices. [6] The survey, form, app or collection tool is on a mobile device such as a smart phone or a tablet.
Observational research is a method of data collection that has become associated with qualitative research. [1] Compared with quantitative research and experimental research, observational research tends to be less reliable but often more valid [citation needed]. The main advantage of observational research is flexibility.
Bibliometrics is the application of statistical methods to the study of bibliographic data, especially in scientific and library and information science contexts, and is closely associated with scientometrics (the analysis of scientific metrics and indicators) to the point that both fields largely overlap.
Data quality assurance is the process of data profiling to discover inconsistencies and other anomalies in the data, as well as performing data cleansing [17] [18] activities (e.g. removing outliers, missing data interpolation) to improve the data quality.