Welcome to the Newsletter page of OpenMinTeD
Knowledge discovery is the process of discovering new information. In text and data mining this happens for example by finding new connections or trends in a large amount of text and data. Ron Daniel is director at the Elsevier Labs. He explains Knowledge Discovery and Knowledge Representation in three short videos.
It was a great honour and opportunity to interact with the Docker community during the meetup in Athens on November 29th. More than 30 people attended our talk ‘A scalable, virtual, flexible workflow infrastructure in OpenMinTeD stack’. The talk covered the software stack responsible for executing Text and Data Mining (TDM) workflows on a distributed cloud environment. The workflow setup greatly overlaps with (but is not limited to) modern containerization technologies and especially Docker.
In the old days, if you would do a search in a search engine, you would get a lot of irrelevant hits that for some reason contained the keyword you used. Nowadays search engines give you much better results, because they put the keyword into context. This new way of searching is called ‘Semantic Search‘. Waleed Ammar of the Allen Intitute for Artificial Ingelligence explains semantic search, the challenges and the state-of-the-art in a few short video clips.
Thomas Margoni and Giulia Dore of the University of Glasgow have developed a matrix and two fact sheets on open science and licensing. They presented the tools at the IP summer summit in Glasgow last June. The tools can help researchers, repository owners and many others with how to use open access licences in the context of text and data mining. Curious? You can access the tools through the links in this blogpost.
Are you ready to develop and share an application or software component for text and data mining (TDM)? Or do you have knowledge resources that you would like to share and integrate with our platform? OpenMinTeD is looking for service providers, innovators, SMEs and researchers who can join and build on the platform! You can apply for this call until 26 January 2018. Winners of the call will be awarded a sum of money to implement their plans. You will also be part of an online hackathon to help you along the way.
Mads Rydahl is the founder of UNSILO, a Danish start-up that applies machine learning to scientific publishing.
Iana Atanassova, Centre Tesnière – CRIT, University of Bourgogne Franche-Comté, is using Text and Data Mining (TDM) to study full-text scientific articles. Studying these papers can be a challenge, as they are usually in a format that is hard to process.