Titre :

Text data mining and data quality management for research information systems in the context of open data and open science

Auteur(s) :

Azeroual, Otmane [Auteur]
Saake, Gunter [Auteur]
Otto-von-Guericke-Universität Magdeburg = Otto-von-Guericke University [Magdeburg] [OVGU]
Abuosba, Mohammad [Auteur]
University of Applied Sciences [Berlin] [HTW]
Schopfel, Joachim [Auteur]
Groupe d'Études et de Recherche Interdisciplinaire en Information et COmmunication - ULR 4073 [GERIICO ]

Titre de la manifestation scientifique :

ICOA 2018 3e colloque international sur le libre accès

Organisateur(s) de la manifestation scientifique :

ESI Rabat

Ville :

Rabat

Pays :

Maroc

Date de début de la manifestation scientifique :

2018-11-28

Titre de la revue :

Actes du 3e colloque international sur le libre accès. Le libre accès à la science : fondements, enjeux et dynamiques

Date de publication :

2018

Mot(s)-clé(s) en anglais :

Current research information system
Data quality
Open data
Open science
Text and data mining
Current research information systems (CRIS)
Research information systems (RIS)
Research information
Standardization
Text analysis
Data mining
Knowledge discovery database
Data quality management
Big data

Discipline(s) HAL :

Sciences de l'Homme et Société/Sciences de l'information et de la communication
Informatique [cs]/Base de données [cs.DB]

Résumé en anglais : [en]

In the implementation and use of research information systems (RIS) in scientific institutions, text data mining and semantic technologies are a key technology for the meaningful use of large amounts of data. It is not the ...
Lire la suite >In the implementation and use of research information systems (RIS) in scientific institutions, text data mining and semantic technologies are a key technology for the meaningful use of large amounts of data. It is not the collection of data that is difficult, but the further processing and integration of the data in RIS. Data is usually not uniformly formatted and structured, such as texts and tables that cannot be linked. These include various source systems with their different data formats such as project and publication databases, CERIF and RCD data model, etc. Internal and external data sources continue to develop. On the one hand, they must be constantly synchronized and the results of the data links checked. On the other hand, the texts must be processed in natural language and certain information extracted. Using text data mining, the quality of the metadata is analyzed and this identifies the entities and general keywords. So that the user is supported in the search for interesting research information. The information age makes it easier to store huge amounts of data and increase the number of documents on the internet, in institutions’ intranets, in newswires and blogs is overwhelming. Search engines should help to specifically open up these sources of information and make them usable for administrative and research purposes. Against this backdrop, the aim of this paper is to provide an overview of text data mining techniques and the management of successful data quality for RIS in the context of open data and open science in scientific institutions and libraries, as well as to provide ideas for their application. In particular, solutions for the RIS will be presented.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Groupement d'Études et de Recherche Interdisciplinaire en Information et Communication (GERiiCO) - ULR 4073

Source :

Harvested from HAL