University of Michigan researcher contributes to NASA findings on carbon in the atmosphere showcased in the journal Science

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High-resolution satellite data from NASA’s Orbiting Carbon Observatory-2 are revealing the subtle ways that carbon links everything on Earth – the ocean, land, atmosphere, terrestrial ecosystems and human activities. Scientists using the first 2 1/2 years of OCO-2 data have published a special collection of five papers today in the journal Science that demonstrates the breadth of this research. In addition to showing how drought and heat in tropical forests affected global carbon dioxide levels during the 2015-16 El Niño, other results from these papers focus on ocean carbon release and absorption, urban emissions and a new way to study photosynthesis. A final paper by OCO-2 Deputy Project Scientist Annmarie Eldering of NASA’s Jet Propulsion Laboratory in Pasadena, California, and colleagues gives an overview of the state of OCO-2 science.

Manish Verma, a Geospatial/Data Science Consultant at the University of Michigan’s Consulting for Statistics, Computing and Analytics Research (CSCAR) unit, contributed as a coauthor to an article on a new way to measure photosynthesis over time and space.

Using data from the OCO-2, Verma’s analysis helped expand the utility of measurements of solar induced fluorescence (SIF), which indicates active photosynthesis in plants. Verma’s work showed that SIF data collected from the OCO-2 satellite provides reliable information on the variability of photosynthesis at a much smaller scale — down to individual ecosystems.

This can, in turn, “lead to more reliable estimates of carbon sources — that is, when, where, why and how carbon is exchanged between land and atmosphere — as well as a deeper understanding of carbon-climate feedbacks,” according to the Science article.

For more, see the NASA press release (https://www.nasa.gov/feature/jpl/new-insights-from-oco-2-showcased-in-science) and the Science article (http://science.sciencemag.org/content/358/6360/eaam5747.full)

Real estate dataset available to researchers

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The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major data resource capturing parcel-level information about the property market in the United States.  

The data were licensed from the Corelogic corporation, who have assimilated deed, tax and foreclosure information on nearly all properties in the entire US. Coverage dates vary by county, some county records go back fifty years. Coverage is more comprehensive from the 1990s to the present.

These data will support a variety of research efforts into regional economies, economic disparities, trends in land-use, housing market dynamics, and urban ecology, among many other areas.

The data are available on the Turbo Research Storage system for users of the U-M High Performance Computing infrastructure, and via the University of Michigan Library.

To access the data, researchers must first sign a MOU; contact Senior Associate Librarian Catherine Morse cmorse@umich.edu for more information, or visit https://www.lib.umich.edu/database/corelogic-parcel-level-real-estate-data.

U-M, SJTU research teams share $1 million for data science projects

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Five research teams from the University of Michigan and Shanghai Jiao Tong University in China are sharing $1 million to study data science and its impact on air quality, galaxy clusters, lightweight metals, financial trading and renewable energy.

Since 2009, the two universities have collaborated on a number of research projects that address challenges and opportunities in energy, biomedicine, nanotechnology and data science.

In the latest round of annual grants, the winning projects focus on data science and how it can be applied to chemistry and physics of the universe, as well as finance and economics.

For more, read the University Record article.

For descriptions of the research projects, see the MIDAS/SJTU partnership page.

Liza Levina, PhD, Chosen IMS Medallion Lecturer in 2019

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Professor Liza Levina has been selected to present an Institute of Mathematical Statistics (IMS) Medallion Lecture at the 2019 Joint Statistical Meeting (JSM).

Each year eight Medallion Lecturers are chosen from across all areas of statistics and probability by the IMS Committee on Special Lectures. The Medallion nomination is an honor and an acknowledgment of a significant research contribution to one or more areas of research. Each Medallion Lecturer will receive a Medallion in a brief ceremony preceding the lecture.

New Data Science Computing Platform Available to U-M Researchers

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Advanced Research Computing – Technology Services (ARC-TS) is pleased to announce an expanded data science computing platform, giving all U-M researchers new capabilities to host structured and unstructured databases, and to ingest, store, query and analyze large datasets.

The new platform features a flexible, robust and scalable database environment, and a set of data pipeline tools that can ingest and process large amounts of data from sensors, mobile devices and wearables, and other sources of streaming data. The platform leverages the advanced virtualization capabilities of ARC-TS’s Yottabyte Research Cloud (YBRC) infrastructure, and is supported by U-M’s Data Science Initiative launched in 2015. YBRC was created through a partnership between Yottabyte and ARC-TS announced last fall.

The following functionalities are immediately available:

  • Structured databases:  MySQL/MariaDB, and PostgreSQL.
  • Unstructured databases: Cassandra, MongoDB, InfluxDB, Grafana, and ElasticSearch.
  • Data ingestion: Redis, Kafka, RabbitMQ.
  • Data processing: Apache Flink, Apache Storm, Node.js and Apache NiFi.

Other types of databases can be created upon request.

These tools are offered to all researchers at the University of Michigan free of charge, provided that certain usage restrictions are not exceeded. Large-scale users who outgrow the no-cost allotment may purchase additional YBRC resources. All interested parties should contact hpc-support@umich.edu.

At this time, the YBRC platform only accepts unrestricted data. The platform is expected to accommodate restricted data within the next few months.

ARC-TS also operates a separate data science computing cluster available for researchers using the latest Hadoop components. This cluster also will be expanded in the near future.

ARC-TS seeks input on next generation HPC cluster

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The University of Michigan is beginning the process of building our next generation HPC platform, “Big House.”  Flux, the shared HPC cluster, has reached the end of its useful life. Flux has served us well for more than five years, but as we move forward with replacement, we want to make sure we’re meeting the needs of the research community.

ARC-TS will be holding a series of town halls to take input from faculty and researchers on the next HPC platform to be built by the University.  These town halls are open to anyone and will be held at:

  • College of Engineering, Johnson Room, Tuesday, June 20th, 9:00a – 10:00a
  • NCRC Bldg 300, Room 376, Wednesday, June 21st, 11:00a – 12:00p
  • LSA #2001, Tuesday, June 27th, 10:00a – 11:00a
  • 3114 Med Sci I, Wednesday, June 28th, 2:00p – 3:00p

Your input will help to ensure that U-M is on course for providing HPC, so we hope you will make time to attend one of these sessions. If you cannot attend, please email hpc-support@umich.edu with any input you want to share.

Job Opening: Research Cloud Administrator

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Advanced Research Computing – Technology Services (ARC-TS)  has an exciting opportunity for a Research Cloud Administrator.

This position will be part of a team working on a novel platform for research computing in the university for data science and high performance computing.  The primary responsibilities for this position will be to develop and create a resource sharing environment to enable execution of Data Science and HPC workflows using containers for University of Michigan researchers.

For more details and to apply, visit: http://careers.umich.edu/job_detail/142372/research_cloud_administrator_intermediate

New private insurance claims dataset and analytic support now available to health care researchers

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The Institute for Healthcare Policy and Innovation (IHPI) is partnering with Advanced Research Computing (ARC) to bring two commercial claims datasets to campus researchers.

The OptumInsight and Truven Marketscan datasets contain nearly complete insurance claims and other health data on tens of millions of people representing the US private insurance population. Within each dataset, records can be linked longitudinally for over 5 years.  

To begin working with the data, researchers should submit a brief analysis plan for review by IHPI staff, who will create extracts or grant access to primary data as appropriate.

CSCAR consultants are available to provide guidance on computational and analytic methods for a variety of research aims, including use of Flux and other UM computing infrastructure for working with these large and complex repositories.

Contact Patrick Brady (pgbrady@umich.edu) at IHPI or James Henderson (jbhender@umich.edu) at CSCAR for more information.

The data acquisition and availability was funded by IHPI and the U-M Data Science Initiative.

MIDAS starting research group on mobile sensor analytics

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The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.

There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.

Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.

Where and When:

Noon to 2 pm, April 13, 2017

School of Public Health I, Room 7625

Lunch provided

Agenda:

  • Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);

  • A brief presentation of a list of funding opportunities;

  • Discussion of research ideas and collaboration in the context of grant application and industry partnership.

Future Plans: Based on the interest of participants, MIDAS will alert researchers to relevant funding opportunities, hold follow-up meetings for continued discussion and team formation as ideas crystalize for grant applications, and work with the UM Business Engagement Center to bring in industry partnership.

Please RSVP.  For questions, please contact Jing Liu, Ph.D, MIDAS research specialist (ljing@umich.edu; 734-764-2750).