Recent Technical Reports and White Papers

  • About data commons and data meshes
  • Ten Pillars for Data Meshes | arxiv |
  • An Annotated Glossary for Data Commons, Data Meshes, and Other Data Platforms | arxiv |

Organizations

Center for Translational Data Science

The Center for Translational Data Science at the University of Chicago (CTDS) is developing the discipline of data science and its applications to problems in biology, medicine, healthcare and the environment. We develop and operate large scale data platforms to support research in topics of societal interest including cancer, cardiovascular disease, veterans’ health, pain management, opioid use disorder, and environmental science. We also develop new machine learning and AI algorithms over the data in our platforms.

Our center has been at the forefront of data sharing by continuously leveraging new approaches and new technology to enable world class science in a variety of fields. We have developed a number of important firsts: including one of the first large scale data clouds (NSF supported Open Science Data Cloud (2010-2016)), the first data cloud designed to host biomedical data and approved as a NIH Trusted Partner (Bionimbus Protected Data Cloud (2013-present)), the first large scale data commons (National Cancer Institute’s Genomic Data Commons (2016-present)), and the first set of services to create data ecosystems or meshes for biomedical data (HEAL Data Platform (2020-present)).

Analytic Strategy Partners

I founded Analytic Strategy Partners (ASP) in 2016 and have been its managing director since then. Analytic Strategy Partners helps companies develop analytic strategies, improve their analytic operations, and evaluate potential analytic acquisitions and opportunities. ASP specializes in helping companies achieve value from analytics by selecting the right analytic opportunity at the right time, providing advice on moving analytics into operations, providing guidance on analytic governance, and explaining the trade-offs of different organizational structures for analytics. ASP brings extensive experience and professionalism to every project, uses best practices when available, and is able to develop new approaches when needed.

Open Commons Consortium

I am a Director of the 501(c)(3) not for profit Open Commons Consortium (OCC). The OCC manages and operates data commons and cloud computing infrastructure to support scientific, medical, health care and environmental research. OCC members span the globe and include over 30 universities, companies, and government agencies.

Open Data Group

I founded Open Data Group in 2002 and was its Managing Partner until 2015. During this period, Open Data provided consulting services so that companies could develop and deploy machine learning and AI models over big data. Open Data also developed open source software to make it easier to deploy machine learning models, such as Augustus. Open Data was also active in the development of open standards for deploying analytics, including the Predictive Model Markup Language (PMML) and the Portable Format for Analytics (PFA), the two leading standards for analytic and machine learning models.

In 2016, Open Data pivoted and began to sell analytic engines designed so that companies could more easily and rapidly deploy analytic modelss and scale up and monitor deployed models using enterprise services. From 2016-2017, I was Open Data's Chief Data Scientist. In 2016, Open Data Group changed its name to ModelOp.