My experience of DCO Data Science Day, 2014
On a drizzly spring day in Troy, NY earlier this month, more than 20 scientist and domain experts from Deep Carbon Community mingled on the occasion of DCO Data Science Day 2014 in the Bruggeman’s Conference Centre of Rensselaer Polytechnic Institute, one of the most prestigious institutions in the country. This being the first conference I was attending since starting my work with Tetherless World Constellation’s Data science group, I was excited to see how things would be when experts from varying domains meet and what was there perspective on Data Science. That being said, I was a novice and had no domain knowledge. So predominantly, I was sitting there trying to make sense of what people were trying to say for most of the time. The mention of terms like data modelling, hosting generic data models on the cloud, visualization etc., sparked my enthusiasm to pay attention to their views and findings.
One of the aspects of the conference that interested me was the breakout sessions since it helped people communicate their views and came out with a number of features that will improve the interactions within the community. Few of the interesting ideas put forward by them that caught my attention were about incorporating a notification mechanism based on their area of expertise and providing suggestions about publications. It was nice to see that social network features were finding applications within the research community for data linking and data sharing. Similarly, the use of several other technologies were welcomed by the community to increase the interaction between them. The ones like creating generic models and making them accessible to a wide range of audience were put forward by many scientists. It was truly an awesome experience which gave me a different perspective about data and how it can be put to use. This also showed the potential of Data Science applications to help these experts unravel intrinsic details of life forms and other chemicals. I hope we can continue our great work in bridging the data needs of these domain experts and explore more applications for Data science.