Text Mining and Agriculture: The AgroNLP projects

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The TETIS team (Territoires, Environnement, Télédetection et Information Spatiale or Land, environment, remote sensing and spatial information in English) is a Joint Research Unit of some of the major French actors in text mining and Natural Language Processing, namely AgroParisTech, Irstea (National Research Institute of Science and Technology for Environment and Agriculture) and Cirad (the International Cooperation Centre for Agricultural Development Research). It is located in Montpellier. The TETIS Unit has been really active in projects related to the application of text mining in use cases in the agricultural sector.

These AgroNLP projects (Natural Language Processing applied to AGRicultural dOmain) aim to address different challenges faced by stakeholders in the agri-food sector, such as:

  • Animal Disease Surveillance: The project proposes a new methodology in the domain of epidemic intelligence in animal health in order to discover knowledge in web documents dealing with animal disease outbreaks.
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Working on text mining – this is what we do

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Our participation in the OpenMinTeD Horizon 2020 project allowed us to get to know a little bit more on text mining, the communities around it, the various types of stakeholders and the issues that they face.

Our job was everything around the user requirements’ elicitation; we were responsible for defining and applying a methodology for creating the profiles of various types of text mining stakeholders, understanding their content-related needs, identifying their issues and proposing the optimal solutions to address them – focusing on the text mining-related ones. Pretty demanding, right?

The project encompasses four (4) different communities:

  1. Scholarly Communication
  2. Agriculture / Biodiversity
  3. Life Sciences
  4. Social Sciences

Our methodology consisted of two rounds of requirements’ elicitation:

i) A general online questionnaire was prepared and project partners were asked to adapt it for their communities.… Click to read the full post

Open Access & Text Mining: Moving Things Forward

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Text mining refers to “the process or practice of examining large collections of written resources in order to generate new information” (source). I am not an expert in text mining, but I understand that it is about applying specialized software/algorithms/techniques on existing textual information so that it can be read and analyzed by machines in order for them to extract more meaningful information for us, humans. Of course, text mining is no news to the research community, as it seems that it all started back in the ’80s with a methodology titled CAVE (Content Analysis of Verbatim Explanations) but its background goes beyond the scope of this article.… Click to read the full post

An Open Science Cloud for Europe’s agri-food research skies

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During these strange, troubling times, Europe seems to be trying to make some steps towards closer collaboration and integration. The strategy for creating a Digital Single Market is one of these desired steps that will try to bring together the 28 member states at the online space. And as far European research is concerned, a major decision has been taken during the past few weeks by some of the key stakeholders that drive the digital science (or eScience) agenda: to join forces and create a so-called European Open Science Cloud for Research.

Five leading Europan initiatives (EUDATLIBEROpenAIREEGI and GEANT) that are working on different parts of e-infrastructures to facilitate research, have published a position paper that describes their joint vision on empowering research data sharing, data stewardship and data reuse in Europe for the benefit of innovation and growth.… Click to read the full post

Text and data mining (TDM) in agri-food research

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A wealth of published research outcomes is currently publicly available (mostly thanks to the really active Open Access initiatives and mandates that keep finding ways to open up even more research data); however, at the same time, researchers are still facing a challenge when seeking for specific elements of a research publication that would support their own research, such as an image, a diagram or a dataset related to a specific topic, such as crop disease, within the scientific literature. Indeed, such components are currently embedded in various types of publications and cannot be identified, described and retrieved as individual entities.… Click to read the full post

New proposals & new projects – an update from the Agro-Know PM team

Spreading the good news!

What a busy period that was. Over the past days we submitted new project proposals, we started working on new projects and we got great news from evaluation results from our past proposals! But let’s take it one by one.

Over the past period we were quite busy working on some new H2020 proposals. Actually, the PM (Project Management) team, under Nikos Manouselis lead, moved to the secondary offices, our Proposal War Room, where we worked all together preparing two very different proposals.

Firstly, we were invited to join a MARIE Skłodowska-Curie Action, in an Innovative Training Network for the call of 2015 under the coordination of Aston University and our close friend Christopher Brewster (@cbrewster).… Click to read the full post