By: Inger Lise Næss // UiT The Arctic University of Norway
Open Polar provides a search tool for freely available research literature and data sets specifically targeting the polar regions, across all subject areas. The portal makes research-based knowledge about the Arctic and the Antarctic more accessible than ever – to researchers, students, policy makers, and the public.
The portal collects metadata from more than 4 600 providers worldwide. About 78% of the records found in the portal are research documents, and 22% are data sets. The total number of records is about 1.8 million and constantly increasing.
Why do we need Open Polar?
As Open Science is gaining momentum, there is a need for powerful discovery tools that can harvest and present research literature and datasets available in open access form – free of charge.
In 2019, around 60% of open access polar records could not be found through searchable platforms, but only via the webpage of the institution holding the record, according to a preliminary report by Tamer Abu-Alam, project leader for Open Polar. This gap demonstrates the need to gather open access records in a homogenous, available platform.
By integrating publications and data sets in the same search, Open Polar speeds up the discovery process, fosters the transparency of research, and minimises duplication of fieldwork and experiments.
The user-friendly interface includes the possibility to search via geolocations on a map, along with other advanced search options.
Fact about Open Polar
Open Polar builds on these fundamental principles:
- Building competence
A small team with a mix of technical competence and scientific background is the core of the project
- Consulting the researcher community. The search portal is built upon feedback from a reference group of active researchers from a variety of research fields
- Utilising existing resources. Open Polar is based on Open-Source software and existing infrastructure
- Accepting the imperfect world. Having duplicates of some data sets is better than missing valuable data sets