Title: Simulation Summarization
Speaker: Nidhi Parikh
As increasingly large-scale multiagent simulations are being implemented, new methods are becoming necessary to make sense of the results of these simulations. Even concisely summarizing the results of a given simulation run is a challenge. Here we pose this as the problem of simulation summarization: how to extract the causally-relevant descriptions of the trajectories of the agents in the simulation. We present a simple algorithm to compress agent trajectories through state space by identifying the state transitions which are relevant to determining the distribution of outcomes at the end of the simulation. We present multiple toy examples to illustrate the working of the algorithm, and then apply it to a complex simulation of a major disaster in an urban area.
Title: Linked Open Data For Ebola Epidemic
Speaker: S.M.Shamimul Hasan
The Ebola disease outbreak in 2014, which killed more than 10,000 people, was one of the largest Ebola outbreaks in the history of mankind. People around the globe are publishing Ebola epidemic data online. Today researchers are overwhelmed with many different types of Ebola datasets available on the web. Most of the datasets are not well organized. Moreover, datasets are not linked. Linking is complicated because of data heterogeneity, and lack of a common data storing scheme. To overcome these limitations, we propose linked open data (LOD) for Ebola datasets. We identified several publicly available Ebola datasets and linked them using LOD principles. Our Ebola linked dataset is a rich Ebola epidemic dataset. That is available in machine-readable form and capable of facilitating future Ebola outbreak. Moreover, it goes beyond making the data available in machine readable form. It creates semantic relationships between them. This allows a rich query set to be formed. It takes a step towards standardization and also makes this data available for public use.
Webex Meeting Num. : 644 714 417