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Data for software projects

I agree with David that obtaining suitable data can be problematic. One of the attractions of bioinformatics is that loads of data is readily available. But mostly I started this thread so discussion could take place under a more sensible title.

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  • 1.

    For this one

    • An open source version of FESA, the Future Energy Scenario Assessment. FESA, put out by Orion Innovations, is proprietary software that models energy systems scenarios, including meteorological data, economic analysis and technology performance.

    the main data needed are historical weather records to estimate wind and solar energy fluctuations, and data for our-by-hour electricity usage. Ideally for the entire world but one could start with whatever regions make such data available.

    The data for

    • An automated species-identification system. See the article Time to automate identification in the journal Nature. The authors say that taxonomists should work with specialists in pattern recognition, machine learning and artificial intelligence to increase accuracy and reduce drudgery.

    is likely to be very disparate. Photos people have taken of dragonflies in their garden, sound recordings of bat echo-location calls, micro-photographs of phytoplankton in the ocean. I hope not all the relevant data is hard to get hold of.

    Comment Source:For this one &bull; An open source version of <a href="http://www.orioninnovations.co.uk/Fesa/downloads/FESAflyerAug2010.pdf">FESA</a>, the Future Energy Scenario Assessment. FESA, put out by <a href="http://www.orioninnovations.co.uk">Orion Innovations</a>, is proprietary software that models energy systems scenarios, including meteorological data, economic analysis and technology performance. the main data needed are historical weather records to estimate wind and solar energy fluctuations, and data for our-by-hour electricity usage. Ideally for the entire world but one could start with whatever regions make such data available. The data for &bull; An automated species-identification system. See the article <a href="http://www.nature.com/nature/journal/v467/n7312/full/467154a.html">Time to automate identification</a> in the journal <i>Nature</i>. The authors say that taxonomists should work with specialists in pattern recognition, machine learning and artificial intelligence to increase accuracy and reduce drudgery. is likely to be very disparate. Photos people have taken of dragonflies in their garden, sound recordings of bat echo-location calls, micro-photographs of phytoplankton in the ocean. I hope not all the relevant data is hard to get hold of.
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