Further conceptual and technical information on DataLad, and applications built on DataLad, are available from the publications listed below.
- The best of both worlds: Using semantic web with JSOB-LD. An example with NIDM Results & DataLad [poster]
Camille Maumet, Satrajit Ghosh, Yaroslav O. Halchenko, Dorota Jarecka, Nolan Nichols, Jean-Baptist POline, Michael Hanke
- One thing to bind them all: A complete raw data structure for auto-generation of BIDS datasets [poster]
Benjamin Poldrack, Kyle Meyer, Yaroslav O. Halchenko, Michael Hanke
- Fantastic containers and how to tame them [poster]
Yaroslav O. Halchenko, Kyle Meyer, Matt Travers, Dorota Jarecka, Satrajit Ghosh, Jakub Kaczmarzyk, Michael Hanke
- YODA: YODA’s Organigram on Data Analysis [poster]
An outline of a simple approach to structuring and conducting data analyses that aims to tightly connect all their essential ingredients: data, code, and computational environments in a transparent, modular, accountable, and practical way.
Michael Hanke, Kyle A. Meyer, Matteo Visconti di Oleggio Castello, Benjamin Poldrack, Yaroslav O. Halchenko
F1000Research 2018, 7:1965 (https://doi.org/10.7490/f1000research.1116363.1)
- Go FAIR with DataLad [talk]
On DataLad’s capabilities to create and maintain Findable, Accessible, Interoperable, and Re-Usable (FAIR) resources.
Michael Hanke, Yaroslav O. Halchenko
Bernstein Conference 2018 workshop: Practical approaches to research data management and reproducibility (slides)
OpenNeuro kick-off meeting, 2018, Stanford (slide sources)