Open Arctic Research Index (Open ARI): A new horizon in archiving and collecting Arctic datasets

• Published in: Septentrio Conference Series
• Main Author: Abu-Alam, Tamer S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Septentrio Academic Publishing 2018
• Subjects: Open ARI; Dataset repositories; Arctic Research; Polar Sciences; Antarctic; Arctic; Ari; Norway; The Antarctic; Antarc*; Arctic University of Norway; UiT The Arctic University of Norway
• Online Access: https://septentrio.uit.no/index.php/SCS/article/view/4567; https://doi.org/10.7557/5.4567

Open ARI is a planned service at UiT The Arctic University of Norway in order to collect, sort and archive all the openly available publications and datasets that were published in the Arctic region. This new service will be available as an open access database to the users through-out an interactive searchable front-end. The pilot project will investigate how such a service can support researchers in their research by making results from Arctic research more visible and better retrievable through a common search index based on a standardized, interdisciplinary metadata set. Moreover and for a better overview for the polar sciences, the new Arctic database will include, as well, examples from the Antarctic region. As a pilot project, we started by clarifying the need for a new technical solution by which the Open ARI will be able to collect all the published material using algorithms that allow the best way of filtering processes. Also we are now in a stage to define all the possible national and international collaborators who can support and feed the Open ARI with content from their internal databases. A group of scientists and researchers will be formed as a reference group who will show us the needs of the scientific community to be sure that our final product will meet the interest of the users. By the end of the pilot project, the team will analyze the success opportunities and the challenges in order to plan a full scale management model.