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Managing data. Why do it?

Managing data. Why do it?. DATA Data was once an innocuous android instead of a method of judging researchers. What is “managing” data?. Data Accessible? Enough storage? Backed up? Metadata Change history?

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Managing data. Why do it?

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  1. Managing data. Why do it? DATA Data was once an innocuous android instead of a method of judging researchers

  2. What is “managing” data? • Data • Accessible? • Enough storage? • Backed up? • Metadata • Change history? • Link to research proposal/experimental design/analysis tools/published papers/...? • Will it be needed for 5, 10, 20 years/lawsuits?

  3. I already know how to do it Yes, but.. have you considered moving: • From the desktop to the (semantic!) web • From small-scale to continental-scale • From disciplinary to multi-disciplinary • From a private collection to a public library • From unfunded to funded • From the academic realm to popular science

  4. In other words.. data sharing Data sharing matters even if you do not share • We all use shared data to some degree • Data sharing is de rigueur in some disciplines • Data sharing is legally required in some cases • Data sharing is necessary for open science • Data sharing is a minimum for collaborations

  5. Benefits of data sharing Public benefits • New research: new results from data reuse • Reproducibility: access to provenance info • Economies of scale: fund projects ones Private benefits • Prestige: promote one’s work in new ways • Career dev: count data as research output • Efficiency: division of labour, streamline research

  6. This requires changes to how data is managed • Data need to be discoverable • Data need to be standardised • Data need to be put in context • Data need to acknowledge contributors • Data need to include use conditions • Data need to link to other relevant resources • (Data need to be peer-reviewed?)

  7. Case study Environmental acoustics • Emerging, inter-disciplinary research • Environmental research using sound recordings of the environment • Used to monitor, analyse the environment • Recordings require sophisticated statistics • No existing theory, method, tool or standard

  8. Growing pains Started on a small scale • Initially used to monitor individual sites • Opportunistic deployment of recorders • Ad hoc management of data • Closed system, inaccessible data • Serves the needs of a small group at QUT • Competes with similar efforts elsewhere

  9. A new opportunity Became part of the Australian supersite Network • Data part of a long-term monitoring program • Deploy recorders at continental scale • Interest in integrating with other data sources • Obligation to publicise and describe data • Requires collaboration with partner sites • Need for storage capacity and server software

  10. From managing data to eResearch Develop better tools for science • Two workshops to define data standards • Build a dedicated acoustic repository • Develop a library of acoustic data tools • Embed recordings with environmental data • Release data under Creative Commons • Release platform as open source

  11. Freebies! New research opportunities • Approached by potential collaborators • Partnerships with community groups (research + linkage) • Special issue of Ecological Informatics Raise public profile of image • Newspaper articles • Radio interviews • Documentary Access to in-kind support • Funding of national deployment of equipment • Access to existing infrastructure and services

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