Title : Disambiguating relations and entities without external knowledge
| Presenter | Tom Kenter |
| Abstract | Open Information Extraction is the task of extracting triples (of relations and the entities they relate) from free text, without any external sources of knowledge, such as, e.g., ontologies or knowledge bases. Disambiguating these entities is an additional task. Which surface forms refer to the same entity? Which relations are semantically similar? We aim to do this disambiguation step in an 'open' fashion, so unsupervised and without any external sources of information. In this talk I will discuss some ideas I have and I hope to receive helpful feedback. This is very much ongoing research, so no tables with smashing results (yet…). |
Title : Effective data management in the Lab!
| Presenter | Dena Tahvildari |
| Abstract | Science means standing on the shoulders of others. The scientific method requires that data generated and method used is exactly recorded, transparent and available for re-use. Current data management practices in academic (food) laboratories do not allow for effective and efficient capture of data by individual researchers. As a result, there are inefficiencies in reusing data to verify, reproduce and build upon the existing experimental results. We want to know if the problem is rooted in individual motivational factors, technology or a combination of the both. For this, we need to understand academic lab research activities in terms of the way researchers keep a record of their experimental processes and also the way they re-use lab data and methods. Based on these findings, we propose set of interventions- combining individual incentives and technical tools- to promote effective and efficient data capture and re-use. We will evaluate our research methods by testing the developed tools among academic lab food researchers. |