Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Assistant Professor Piotr Majka, Nencki Institute of Experimental Biology, Poland
- Second opponent: Senior Research Librarian Ingrid Heggland, NTNU: Norwegian University of Science and Technology,
- Third member and chair of the evaluation committee: Researcher Einar Høgestøl, University of Oslo
Chair of the Defence
Associate Professor Jan Magnus Aronsen, University of Oslo
Principal Supervisor
Professor Trygve B. Leergaard, University of Oslo
Summary
Recently, increasing amounts of brain data have been made available in data portals to potentially be discovered, interpreted, and integrated into new insights for neuroscience. However, this research process is rarely straightforward and often at halt. The main challenges for neuroscience are the complexity of the brain, the heterogeneity of approaches to study it, the multimodality of data output, and the deluge of data without proper annotation of metadata. These challenges complicate our opportunities to discover and interpret brain data, and to move forward with integration and understanding.
The FAIR guiding principles, introduced in 2016, provide solutions to improve the findability, accessibility, interoperability, and reusability of shared research data. Location metadata, or positions within brain atlases related to a specific set of research data, are possible to document and register for all data originating from the brain and may act as a common denominator for both discovery and data integration. Digital three-dimensional (3D) brain atlases are independent of the plane of sectioning and allow researchers to express precise information about anatomical structures and positions using brain atlas coordinates. Inspired by the FAIR principles as well as opportunities presented by 3D brain atlases, we have established new solutions for finding and integrating relevant research data from the brain.
In this Thesis, I present two workflows. The first is a workflow for sharing research data, while the other is a workflow for integrating neuroscientific data based on anatomical location in 3D brain atlases. Next, we may utilise these to develop a platform for spatially indexing and co-visualising shared brain data in 3D atlas space, to better find and reuse relevant research data and integrate them into new insights for neuroscience.
Additional information
Contact the research support staff.