Reference : The Structure of Behavioral Data
E-prints/Working papers : Already available on another site
Social & behavioral sciences, psychology : Multidisciplinary, general & others
http://hdl.handle.net/10993/46533
The Structure of Behavioral Data
English
Defossez, Aurélien [> >]
Ansarinia, Morteza mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)]
Clocher, Brice mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)]
Schmück, Emmanuel mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)]
Schrater, Paul [> >]
Cardoso-Leite, Pedro mailto [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)]
2020
No
[en] For more than a century, scientists have been collecting behavioral data--an increasing fraction of which is now being publicly shared so other researchers can reuse them to replicate, integrate or extend past results. Although behavioral data is fundamental to many scientific fields, there is currently no widely adopted standard for formatting, naming, organizing, describing or sharing such data. This lack of standardization is a major bottleneck for scientific progress. Not only does it prevent the effective reuse of data, it also affects how behavioral data in general are processed, as non-standard data calls for custom-made data analysis code and prevents the development of efficient tools. To address this problem, we develop the Behaverse Data Model (BDM), a standard for structuring behavioral data. Here we focus on major concepts in behavioral data, leaving further details and developments to the project's website (https://behaverse.github.io/data-model/).
http://hdl.handle.net/10993/46533
http://arxiv.org/abs/2012.12583
preprint
https://arxiv.org/abs/2012.12583
FnR ; FNR11242114 > Pedro Cardoso-leite > DIGILEARN > Scientifically Validated Digital Learning Environments > 01/06/2017 > 31/05/2022 > 2016

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