000905196 001__ 905196 000905196 005__ 20220131120448.0 000905196 0247_ $$2doi$$a10.7490/F1000RESEARCH.1118575.1 000905196 037__ $$aFZJ-2022-00479 000905196 1001_ $$0P:(DE-Juel1)178612$$aWagner, Adina Svenja$$b0$$eCorresponding author$$ufzj 000905196 1112_ $$aOrganisation for Human Brain Mapping$$cMontreal (virtual)$$d2021-06-21 - 2021-06-25$$gOHBM$$wUSA 000905196 245__ $$aA pragmatic approach to reusable research outputs 000905196 260__ $$c2021 000905196 3367_ $$033$$2EndNote$$aConference Paper 000905196 3367_ $$2BibTeX$$aINPROCEEDINGS 000905196 3367_ $$2DRIVER$$aconferenceObject 000905196 3367_ $$2ORCID$$aCONFERENCE_POSTER 000905196 3367_ $$2DataCite$$aOutput Types/Conference Poster 000905196 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1642068253_25571$$xOther 000905196 520__ $$aScience is an incremental process that produces and builds on more than journal articles¹. Code, data, results, or tools of previous finished or unfinished projects (research outputs) fuel new undertakings.Reusing research objects allows for reproduction, verification, and extending existing work, evidence synthesis, and minimizing duplicate efforts². The more reusable outputs are, at any stage of a project, the better. The FAIR principles³ center around richly curated metadata to reach maximal reusability. In practice, creating fully FAIR resources is difficult in systems that yet lack or fail to incentivize the necessary standards and procedures. But reusability should be improved nevertheless.We highlight four widely accessible strategies that can elevate reusability as a byproduct of pragmatic research data management, even when compliance to FAIR is not yet possible. ¹ Mons, B. (2018). Data Stewardship for Open Science: Implementing FAIR Principles. CRC Press. ISBN 9780815348184² Thanos, C. (2017). Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies. doi.org/10.3390/publications5010002³ Wilkinson, M. D. et al., (2016). The FAIR Guiding Principles for scientific data management and stewardship. doi.org/10.1038/sdata.2016.18 000905196 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0 000905196 588__ $$aDataset connected to DataCite 000905196 7001_ $$0P:(DE-HGF)0$$aPoline, Jean-Baptiste$$b1 000905196 7001_ $$0P:(DE-Juel1)177087$$aHanke, Michael$$b2$$ufzj 000905196 773__ $$a10.7490/F1000RESEARCH.1118575.1 000905196 8564_ $$uhttps://f1000research.com/posters/10-492 000905196 909CO $$ooai:juser.fz-juelich.de:905196$$pVDB 000905196 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178612$$aForschungszentrum Jülich$$b0$$kFZJ 000905196 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)177087$$aForschungszentrum Jülich$$b2$$kFZJ 000905196 9131_ $$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 000905196 9141_ $$y2021 000905196 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0 000905196 980__ $$aposter 000905196 980__ $$aVDB 000905196 980__ $$aI:(DE-Juel1)INM-7-20090406 000905196 980__ $$aUNRESTRICTED