001040651 001__ 1040651
001040651 005__ 20250317202728.0
001040651 037__ $$aFZJ-2025-01985
001040651 1001_ $$0P:(DE-Juel1)177087$$aHanke, Michael$$b0$$eCorresponding author
001040651 1112_ $$adeRSE25 -  5th conference for Research Software Engineering in Germany$$cKarlsruhe$$d2025-02-26 - 2025-02-26$$wGermany
001040651 245__ $$aDataLad: 10+ years of academic software development
001040651 260__ $$c2025
001040651 3367_ $$033$$2EndNote$$aConference Paper
001040651 3367_ $$2BibTeX$$aINPROCEEDINGS
001040651 3367_ $$2DRIVER$$aconferenceObject
001040651 3367_ $$2ORCID$$aCONFERENCE_POSTER
001040651 3367_ $$2DataCite$$aOutput Types/Conference Poster
001040651 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1742212937_12053$$xAfter Call
001040651 520__ $$aDataLad (Halchenko et al., 2021 [1]) is free and open source software for managing digital objects and their relationship built on top of Git and git-annex. Its initial commit in 2013 marked the beginning of a more than 10 year long academic software history so far, supported by various grants, institutions, and underlying research endeavors. Over time, the software became an extendable ecosystem, addressing a broad range of data logistics challenges in a core library and many extension packages, growing both in features and contributor community. In turn, it also sparked development and grant support in git-annex, a crucial software with a bus factor of 1. Navigating the research software waters of changing affiliations, developer churn, research obligations, and a modular architecture that offers flexibility, but also bears a potential for complexity and fragility, has never been easy.In this contribution, we want to give a case-study-like overview of the lifetime of this research software so far, reflect on the design and development decisions we have made over the years and their advantages or shortcomings, share lessons learned, and give an outlook into the future of the software ecosystem.
001040651 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001040651 7001_ $$0P:(DE-Juel1)178612$$aWagner, Adina Svenja$$b1$$ufzj
001040651 7001_ $$0P:(DE-Juel1)177088$$aWaite, Alexander$$b2$$ufzj
001040651 7001_ $$0P:(DE-Juel1)178613$$aPoldrack, Benjamin$$b3$$ufzj
001040651 7001_ $$0P:(DE-Juel1)184661$$aMönch, Christian$$b4$$ufzj
001040651 7001_ $$0P:(DE-Juel1)178653$$aWaite, Laura$$b5$$ufzj
001040651 7001_ $$0P:(DE-HGF)0$$aWierzba, Małgorzata$$b6
001040651 7001_ $$0P:(DE-Juel1)190195$$aSzczepanik, Michał$$b7$$ufzj
001040651 7001_ $$0P:(DE-Juel1)187419$$aHeunis, Stephan$$b8$$ufzj
001040651 7001_ $$0P:(DE-HGF)0$$aHalchenko, Yaroslav$$b9
001040651 909CO $$ooai:juser.fz-juelich.de:1040651$$pVDB
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)177087$$aForschungszentrum Jülich$$b0$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178612$$aForschungszentrum Jülich$$b1$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)177088$$aForschungszentrum Jülich$$b2$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178613$$aForschungszentrum Jülich$$b3$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)184661$$aForschungszentrum Jülich$$b4$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178653$$aForschungszentrum Jülich$$b5$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)190195$$aForschungszentrum Jülich$$b7$$kFZJ
001040651 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)187419$$aForschungszentrum Jülich$$b8$$kFZJ
001040651 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5254$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001040651 9141_ $$y2025
001040651 920__ $$lyes
001040651 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0
001040651 980__ $$aposter
001040651 980__ $$aVDB
001040651 980__ $$aI:(DE-Juel1)INM-7-20090406
001040651 980__ $$aUNRESTRICTED