Analysis, interpretation and validation of open source data
Advanced Sciences and Technologies for Security Applications, ISSN: 2363-9466, Page: 95-110
2016
- 3Citations
- 11Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Book Chapter Description
A key component for turning open source data and information into open source intelligence occurs during the analysis and interpretation stages. In addition, verification and validation stages can turn this OSINT into validated OSINT, which has a higher degree of credibility. Due to the wide range of data types that can be extracted from open information sources, the types of data analysis that can be performed on this data is specific to the type of data that we have. This chapter presents a set of analysis processes that can be used when encountering specific types of data regardless of what that data is concerning. These methods will assist an open source investigator in getting the most from their data as well as preparing it for further analysis using visualisation and visual analytics techniques for exploration and presentation.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85075806632&origin=inward; http://dx.doi.org/10.1007/978-3-319-47671-1_7; https://link.springer.com/10.1007/978-3-319-47671-1_7; https://dx.doi.org/10.1007/978-3-319-47671-1_7; https://link.springer.com/chapter/10.1007/978-3-319-47671-1_7
Springer Science and Business Media LLC
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