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  • AgriXiv Preprints for Agriculture and Allied Sciences

    On 14 February 2017, the preprint AgriXiv site was launched with support from Open Science Framework (OSF), as part of fulfilling its objective of “development of community e-infrastructure, capacity building and framework for policies related to Open Access, Open Data and Open Education”.___________________________________________________________________________________________________“Everything else can wait, but not Agriculture”, - Jawaharlal ...
  • Open Science 101 project

    Open Science 101 initiative aims to develop an open science curriculum (and teaching materials) for the general concepts underlying the practices of Open Science. ___________________________________________________________________________________________________What is Open? (Open Knowledge International). The principles and facets of Open Science (Open Access, Open Data, Open Licences, Open Peer Review, Open educational resources, etc.) have ...
  • Join the second A.S.I.R.A.'s free Webinar !

    A.S.I.R.A. (Access to Scientific Information Resources in Agriculture) Online Course for Low-Income Countries started on 13 February, 2017. Throughout the course, several webinar sessions will be held based on  the subjects taught in the units. These webinars are open to anyone who is interested in the subject. The ...
  • Free Webinar: Lending to Farmers Using Nontraditional Data

     Online Event: Alternative Data for Financial Decisions: Lending to Farmers Using Nontraditional Data Date & TimeWednesday, February 15, 20174:00 pm Europe Time (Brussels, GMT+01:00) Change time zoneDuration1 hour 15 minutesDescriptionHow do lending institutions make decisions if large portions of the agriculture sector operate in value chains that are informally organized and outside formal systems?...
  • FAIR Principles – review in context of 4TU.ResearchData

    The Dutch archive for the technical sciences - 4TU.ResearchData - has recently analysed itself in the context of the FAIR (Findable, Accessible, Interoperable and Re-usable) data principles. Below is an overview of the metadata that describes each dataset according to the following attributes: FAIR Principles (as scoring matrix) - 4...