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

Makhlouf Shabou, Basma (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Tièche, Julien (City Archives of Montreux, Switzerland) ; Knafou, Julien (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Gaudinat, Arnaud (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale)

This paper aims to describe an interdisciplinary and innovative research conducted in Switzerland, at the Geneva School of Business Administration HES-SO and supported by the State Archives of Neuchâtel (Office des archives de l'État de Neuchâtel, OAEN). The problem to be addressed is one of the most classical ones: how to extract and discriminate relevant data in a huge amount of diversified and complex data record formats and contents. The goal of this study is to provide a framework and a proof of concept for a software that helps taking defensible decisions on the retention and disposal of records and data proposed to the OAEN. For this purpose, the authors designed two axes: the archival axis, to propose archival metrics for the appraisal of structured and unstructured data, and the data mining axis to propose algorithmic methods as complementary or/and additional metrics for the appraisal process.


Keywords:
Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG - Genève
Institute:
CRAG - Centre de Recherche Appliquée en Gestion
Subject(s):
Sciences de l'information
Date:
2020-07
Pagination:
26 p.
Published in:
Records management journal
Numeration (vol. no.):
To be published
DOI:
ISSN:
0956-5698
Appears in Collection:



 Record created 2020-07-08, last modified 2020-07-10

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