Document Type

Article

Source of Publication

Publications

Publication Date

11-14-2023

Abstract

This article describes a complex CRIS (current research information system) implementation project involving the migration of around 120,000 legacy publication records from three different systems. The project, undertaken by Tampere University, encountered several challenges in data diversity, data quality, and resource allocation. To handle the extensive and heterogenous dataset, innovative approaches such as machine learning techniques and various data wrangling tools were used to process data, correct errors, and merge information from different sources. Despite significant delays and unforeseen obstacles, the project was ultimately successful in achieving its goals. The project served as a valuable learning experience, highlighting the importance of data quality and standardized practices, and the need for dedicated resources in handling complex data migration projects in research organizations. This study stands out for its comprehensive documentation of the data wrangling and migration process, which has been less explored in the context of CRIS literature.

ISSN

2304-6775

Publisher

MDPI AG

Volume

11

Issue

4

First Page

49

Last Page

49

Disciplines

Computer Sciences | Library and Information Science

Keywords

current research information system (CRIS), research information, data migration, legacy data, data quality, machine learning, data wrangling, natural language processing (NLP)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexed in Scopus

no

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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