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Collaborative platforms for streamlining workflows in Open Science

Collaborative platforms for streamlining workflows in Open Science






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    Collaborative platforms for streamlining workflows in Open Science Collaborative platforms for streamlining workflows in Open Science Presentation Transcript

    • Collaborative platforms for streamlining workflows in Open ScienceKonrad U. F¨rstner, Gregor Hagedorn, Claudia Koltzenburg, o M. Fabiana Kubke, Daniel Mietchen July 30th, 2011 – OKCon 2011, Berlin
    • About this work Wiki base version of the manuscript: http://is.gd/openworkflows
    • Problem: There are many gaps in the scientific process Time consuming and often annoying Loss of informationhttp://www.flickr.com/photos/eirikref/403363597 – CC-BY by flick user eirikref
    • A proposal for improved scientific workflow Seamless transition from bench to publication Based on Virtual Research Environments (VRE) Transparency, reproducibility & reusability Formalization Reputation system includedhttp://commons.wikimedia.org/wiki/File:Future73nb.jpg – PD
    • Conception and project planning Utilizing collective intelligence Management tools can help to handle complex projectshttp://www.flickr.com/photos/marksurman/3604105727/ – CC-BY by flick user marksurman
    • Experiments and data generation More automation needed (ideally via Open Hardware) Formal language to design/program experimentshttp://www.flickr.com/photos/kaibara/2072160194/ – CC-BY by flick user kaibara
    • Data storage = data release Publish data immediately in a machine-readable form Every entity gets an unique identifiers (⇒ referable)http://www.flickr.com/photos/wilhei/109404222/ – CC-BY by flick user wilhei
    • Data analysis Scripting / programming or recording of GUI-tool actions Good examples: Taverna or Galaxy Grid computing if needed / possiblehttp://commons.wikimedia.org/wiki/File:Plastic_tape_measure.jpg – CC-BY by Wimedia Commons user Pastorius
    • Knowledge generation Again: Collaborative - increase the number of brains involved Again: Formalization - e.g. argument maps which link to results and literaturehttp://www.flickr.com/photos/diana_blackwell/2597258115/ – CC-BY by flick user diana blackwell
    • Final publication Little effort: linking to the major outcomes and putting them into the scientific contexthttp://www.flickr.com/photos/yorkjason/3265889476/ – CC-BY by flickr user yorkjason
    • Implementation - Technology Most needed building blocks are available (as FLOSS) – “just” need to be connected Open standards needed Domain specific solutions should be created by the communitieshttp://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev
    • Implementation - Reputation Microcontribution ⇒ Microattribution (e.g. ORCID based)http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev
    • Implementation - Licenses Ideally: Public domain / CC0 (see Panton Principle)http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircel
    • Implementation - Funding Long term aim: Funding agencies require the usage of such Open Science workflows (worked for OA)– CC-BY by flickr user therichbrooks
    • Dealing with the cultural clash via a gradual approach Proposed infrastructure but with fine granular access control and a smaller number of participants.http://www.everystockphoto.com/photo.php?imageId=1761122 – source: The Library of Congress
    • Take home messages in a nut shell All steps of the research process can be represented in / connected to VREs Gaps between the steps are minimized Gain of transparency, reproducibility & reusability Main problems are not technical but cultural/politicalhttp://www.flickr.com/photos/marcoarment/3129076932 – CC-BY by flickr user marcoarment
    • http://www.flickr.com/photos/nateone/3768979925/ – CC-BY by flick user nateone