000873986 001__ 873986
000873986 005__ 20240313094947.0
000873986 037__ $$aFZJ-2020-01148
000873986 041__ $$aEnglish
000873986 1001_ $$0P:(DE-Juel1)161295$$aSprenger, Julia$$b0$$eCorresponding author$$ufzj
000873986 1112_ $$a20th Free and Open source Software Developers' European Meeting$$cBrussels$$d2020-02-01 - 2020-02-01$$gFOSDEM 20$$wBelgium
000873986 245__ $$aChallenges and opportunities in scientific software development - An example from the neurosciences
000873986 260__ $$c2020
000873986 3367_ $$033$$2EndNote$$aConference Paper
000873986 3367_ $$2DataCite$$aOther
000873986 3367_ $$2BibTeX$$aINPROCEEDINGS
000873986 3367_ $$2DRIVER$$aconferenceObject
000873986 3367_ $$2ORCID$$aLECTURE_SPEECH
000873986 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1582281110_17377$$xAfter Call
000873986 502__ $$cRWTH Aachen
000873986 520__ $$aThe approaches used in software development in an industry setting and a scientific environment are exhibit a number of fundamental differences. In the former industry setting modern team development tools and methods are used (version control, continuous integration, Scrum, ...) to develop software in teams with a focus on the final software product. In contrast, in the latter scientific environment a large fraction of scientific code is produced by individual scientists lacking thorough training in software development with a specific research goal in mind. Indeed, it is only in the last decades that scientific software development started to become a fully recognized part of scientific work. Still, formal training in software development is largely missing in the scientific curricula of many universities. Additionally, due to the exploratory nature of the scientific method at the frontier of knowledge, most projects require the implementation of custom code. The combination of these circumstances promotes the development of scientific code not suited for sharing and long term maintenance, limiting the reusability and reproducibility of scientific data and findings. The systematic development and adoption of open source packages by the scientific community can emend this situation. Here we present examplary open source packages from the field of neuroscience and discuss the special requirements for open source software development and services in this research area.
000873986 536__ $$0G:(DE-HGF)POF3-571$$a571 - Connectivity and Activity (POF3-571)$$cPOF3-571$$fPOF III$$x0
000873986 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
000873986 8564_ $$uhttps://fosdem.org/2020/schedule/event/open_research_science_soft_dev/
000873986 909CO $$ooai:juser.fz-juelich.de:873986$$pec_fundedresources$$pVDB$$popenaire
000873986 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161295$$aForschungszentrum Jülich$$b0$$kFZJ
000873986 9131_ $$0G:(DE-HGF)POF3-571$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vConnectivity and Activity$$x0
000873986 9141_ $$y2020
000873986 920__ $$lno
000873986 9201_ $$0I:(DE-Juel1)INM-10-20170113$$kINM-10$$lJara-Institut Brain structure-function relationships$$x0
000873986 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x1
000873986 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x2
000873986 980__ $$aconf
000873986 980__ $$aVDB
000873986 980__ $$aI:(DE-Juel1)INM-10-20170113
000873986 980__ $$aI:(DE-Juel1)INM-6-20090406
000873986 980__ $$aI:(DE-Juel1)IAS-6-20130828
000873986 980__ $$aUNRESTRICTED
000873986 981__ $$aI:(DE-Juel1)IAS-6-20130828