PyBIDS: Python tools for BIDS datasets

Medientyp: E-Artikel

Titel: PyBIDS: Python tools for BIDS datasets

Beteiligte: Yarkoni, Tal [VerfasserIn]; Markiewicz, Christopher [VerfasserIn]; Hayot-Sasson, Valérie [VerfasserIn]; Nielson, Dylan [VerfasserIn]; Carlin, Johan [VerfasserIn]; Kiar, Gregory [VerfasserIn]; Whitaker, Kirstie [VerfasserIn]; DuPre, Elizabeth [VerfasserIn]; Wagner, Adina Svenja [VerfasserIn]; Tirrell, Lee [VerfasserIn]; Jas, Mainak [VerfasserIn]; Hanke, Michael [VerfasserIn]; de la Vega, Alejandro [VerfasserIn]; Poldrack, Russell [VerfasserIn]; Esteban, Oscar [VerfasserIn]; Appelhoff, Stefan [VerfasserIn]; Holdgraf, Chris [VerfasserIn]; Staden, Isla [VerfasserIn]; Thirion, Bertrand [VerfasserIn]; Kleinschmidt, Dave [VerfasserIn]; Lee, John [VerfasserIn]; di Castello, Matteo [VerfasserIn]; Notter, Michael [VerfasserIn]; Gorgolewski, Krzysztof [VerfasserIn]; [...]

Erschienen: Forschungszentrum Jülich: JuSER (Juelich Shared Electronic Resources), 2019

Sprache: Englisch

DOI: https://doi.org/10.21105/joss.01294

ISSN: 2475-9066

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Beschreibung: Brain imaging researchers regularly work with large, heterogeneous, high-dimensional datasets. Historically, researchers have dealt with this complexity idiosyncratically, with every lab or individual implementing their own preprocessing and analysis procedures. The resulting lack of field-wide standards has severely limited reproducibility and data sharing and reuse.To address this problem, we and others recently introduced the Brain Imaging Data Standard (BIDS; (Gorgolewski et al., 2016)), a specification meant to standardize the process of representing brain imaging data. BIDS is deliberately designed with adoption in mind; it adheres to a user-focused philosophy that prioritizes common use cases and discourages complexity. By successfully encouraging a large and ever-growing subset of the community to adopt a common standard for naming and organizing files, BIDS has made it much easier for researchers to share, reuse, and process their data (Gorgolewski et al., 2017).The ability to efficiently develop high-quality spec-compliant applications itself depends to a large extent on the availability of good tooling. Because many operations recur widely across diverse contexts—for example, almost every tool designed to work with BIDS datasets involves regular file-filtering operations—there is a strong incentive to develop utility libraries that provide common functionality via a standardized, simple API.PyBIDS is a Python package that makes it easier to work with BIDS datasets. In principle, its scope includes virtually any functionality that is likely to be of general use when working with BIDS datasets (i.e., that is not specific to one narrow context). At present, its core and most widely used module supports simple and flexible querying and manipulation of BIDS datasets. PyBIDS makes it easy for researchers and developers working in Python to search for BIDS files by keywords and/or metadata; to consolidate and retrieve file-associated metadata spread out across multiple levels of a BIDS hierarchy; to ...

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