Algorithmic methods to explore the automation of the appraisal of structured and unstructured digital data

What is it about?

The main results demonstrate the feasibility of measuring the value of data and records with a reproducible method. More specifically, for the Axis 1, we applied the metrics in a flexible and modular way. We defined also the main principles needed to enable computational scoring method. The results obtained through the expert’s consultation on the relevance of 42 metrics indicate an acceptance rate above 80%. In addition, the results show that 60% of all metrics can be automated. Regarding the Axis 2, 33 functionalities were developed and proposed under six main types: macro analysis, microanalysis, statistics, retrieval, administration, and finally the decision modeling and machine learning. The relevance of metrics and functionalities is based on the theoretical validity and computational character of their method. These results are largely satisfactory and promising.

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