Future TDM’s policy recommendations

logo-futuretdm-h150While discussions at the EU on copyright reform and an exception for text and data mining (TDM) are very much live, FutureTDM, a Commission funded project of TDM experts has, for the past year, already been gathering information, mapping the TDM landscape and listening to the wide variety of individuals and organisations involved in data analytics. The project has just produced the first in a series of reports, providing a range of stakeholders with recommendations to improve TDM uptake in the EU. This FutureTDM policy framework document sets out high-level principles and recommendations.

Studying interdisciplinarity

frederico-nanniFrederico Nanni was not always a text miner. He actually started out as a historian and then switched to digital humanities. During his PhD, he developed a method to detect interdisciplinary research, based on scientific abstracts. Now, he finds text mining fascinating and thinks more historians should learn how to do it.

Evaluating the impact of research

drahomira-hermannovaIt took some time for Drahomira Hermannova to see the value of her research topic, but now she thinks it is the best topic she could ever choose: using text and data mining to evaluate which research can change the world. Not only can this help scientists, it may change the way research is done altogether.

Text Mining for social sciences – tackling the challenges to make search systems smarter

9hi8ujmsdza-braden-collumIn the OpenMinTeD project, partners from different scientific communities are involved to make sure the OpenMinTeD infrastructure will address their needs. As regards the social sciences, a useful application for text mining is the improvement of literature search and information interlinking. To this end, three main challenges were identified: named entity recognition, automatic keyword assignment to texts and automatic detection of mentions of survey variables. This post gives an overview of these tasks and the progress of work so far.