Indiana University Integrative Data Science Lab (IDSL)
Welcome to the Integrative Data Science Lab (IDSL) in Indiana University's School of Informatics, Computing, and Engineering. Integrative Data Science brings together diverse data sets, technologies and expertise with linked data, machine learning and data science approaches to solve real world problems. We are pioneering both infrastructures for integrative data science and domain applications of these infrastructures. The IDSL is directed by David Wild. Here are some of the areas we are applying integrative data science:
Accelerating drug discovery and
reducing clinical trails failures
We are pioneering new ways to accelerate drug discovery, including making better decisions earlier, avoiding expensive failures in clinical trails, and finding the right treatments for the right patients. We developed Chem2Bio2RDF, the first large scale semantic linked data repository for preclinical drug discovery, novel link prediction and data mining algorithms for finding hidden insights in large heterogeneous data networks, and in our 2012 Drug Discovery Today paper laid out a strategy for using semantic technologies and data science to avoid some of the perils of single-target drug discovery. Current projects include researching knowledge networks that encode computable networks for multi-mechanism complex diseases, integrating patient medical records with molecular data to help identify potential targeted therapies, and accelerating drug discovery with automated synthesis and machine learning. We are thankful to NIH NCATS, Indiana CTSI, the OpenPHACTS foundation, Eli Lilly, and Pfizer for funding of this work. Applications in this area are being commercialized in our company Data2Discovery Inc.
Emergency Response & Management
Improving outcomes in disasters and emergency response by smart integration of unconventional datasets, expertise and technologies
We live in an era of profound risk and uncertainty, with climate change, healthcare challenges, pervasive technology, infrastructure vulnerabilities, and cybersecurity all creating new and enhanced threats at local, regional and national levels. We are researching highly creative ways that data from unconventional sources and low cost technologies can be used together to help emergency managers, emergency responders and citizens better understand, prepare for, mitigate and respond to this new landscape. We are re-imagining situational awareness, emergency protocols and resource planning in a world awash with data and technology. We are doing this this through strong partnerships at the local, regional and national level with city government, fire, police and EMS departments and data providers.
Regional Economic Development
Identifying precision policy changes through data science
Through a $1.4m grant from the Economic Development Agency (EDA) and in collaboration with the Center for Complex Networks and Systems Research and the Indiana Business Research Center at IU, we are researching how Data Science, Complex Adaptive Systems and Social Sciences can come together to identify precision policy changes to promote regional economic development. We are doing this through a linked data ecosystem that maps together non-traditional and unconventional datasets, and advanced data gathering and data mining techniques.
Interested in learning Cheminformatics?
We no longer offer formal degrees, but some of our learning materials and a PDF/Kindle eBook are available at LearnCheminformatics.com