Data science has become relevant across all disciplines in areas of STEM from healthcare to environmental studies and cybersecurity, to the humanities and social sciences in areas like criminal justice, ethics, and economics. Now more than ever it is imperative that we work towards developing valuable insights from data science […]
On February 19th, 2021, 280+ students, educators and data science enthusiasts gathered for the Northeast Student Data Corps (NSDC)’s Inaugural Data Science Career Panel, where an esteemed panel of invited speakers shared their experiences and advised the attendees on potential opportunities in Data Science. The session also saw the launch […]
During February’s COVID Information Commons (CIC) webinar, researchers, students, and non-profit leaders gathered to discuss and collaborate on research about COVID. The webinar featured talks from seven scientists from across the nation who shared insights on their NSF-funded research. Speakers included Naomi Senehi from Rice University, Nicola Sochacka from the […]
Guest post by Dr. Sara Stoudt, Lecturer in Statistical and Data Sciences Program, Smith College We’ve all been acutely aware of screens lately; we cannot seem to escape them. As statisticians and data scientists we’re stereotypically buried in our spreadsheets and charts anyway, but who do we exclude when communicating […]
On Wednesday, January 13, 2021, seven scientists from across the nation joined us as part of the ongoing COVID-19 Research Webinar series organized through the COVID Information Commons. During the event, each researcher shared their work, providing new insights regarding the global pandemic and revealed some of the unexpected implications […]
Over 80 people convened for this month’s COVID webinar, as six NSF Rapid Response Research investigators from across the United States shared their research topics and findings regarding the COVID-19 pandemic, and the new COVID Information Commons Student Paper Challenge was announced. This month’s presenters included Foad Hamidi (University of […]
On October 13, 2020, Executive Director Florence Hudson spoke at the Careers in Science program at Iona College. She discussed leveraging data to identify new insights that can help members of society make better decisions, as well as her own career trajectory in science. Representing the current strides and efforts […]
This month’s Covid Information Commons (CIC) webinar brought together researchers, students and leaders in nonprofits. The CIC serves as a platform for researchers and scientists to share knowledge and collaborate on research about COVID. This month, the CIC project team announced the launch of a new feature at covidinfocommons.net: the […]
Eight scientists spoke with an enthusiastic community at the second COVID-19 Research Webinar organized by the COVID Information Commons on October 16, 2020. Presenters who shared their latest research findings regarding the current pandemic included Rachel Wu (University of California-Riverside), Sara Rampazzi (University of Michigan), Sarah Bowman (Hauptman-Woodward Medical Research […]
Study to set groundwork to build machine learning models that rapidly analyze how a virus spreads In April when New York City was under a strict lockdown, a team of 16 student researchers from New York University’s Tandon School of Engineering commenced a National Science Foundation Rapid Response Research (RAPID) […]
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Guest post by Catherine Cramer, Founder and Principal, Woods Hole Institute. The Northeast Big Data Innovation Hub supports the work of DS4All and has done so since 2015. While there are several different strands to this work, the focus on data science in K-12 education continues to be prominent. The […]
The CAREERS Cyberteam Program is a 3-year initiative to build a regional pool of Research Computing Facilitators to support researchers at small and midsized institutions…
Guest post by Jerad Bales, Executive Director, CUAHSI The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) located in Cambridge, MA, has been selected to be the Coordinating Hub for the National Science Foundation’s Critical Zone (CZ) Collaborative Network. The 5-year cooperative agreement became effective September 1, 2020. The […]
CUAHSI’s Compute Services enable education and research in the cloud. In addition to tools that enable data discovery and publication, CUAHSI develops and maintains cloud software to interoperate with CUAHSI’s data repositories to provide analysis, publication, and replication of scientific models and workflows. CUAHSI JupyterHub CUAHSI JupyterHub is a cloud service […]
The COVID-19 pandemic has had a significant impact on the US food supply network. Supply chains that were very efficient in meeting the needs of restaurants and supermarkets have had a hard time adapting to changing conditions.
The COVID-19 pandemic has had a significant impact on the US food supply network. Supply chains that were very efficient in meeting the needs of restaurants and supermarkets have had a hard time adapting to changing conditions.
We tried to understand to what extent people coming from a COVID-19-infected environment interact with the built and natural environment. Specifically, we wanted to understand in three dimensions what people touched, how much they touched, and where they went coming out of hospitals and urgent care facilities at the peak of the COVID-19 outbreak.
Our research examines and compares people’s compliance with these measures over time, across diverse national, cultural, and political contexts. Specifically, it focuses on how different value and belief systems influence (non)compliance with containment measures as the pandemic unfolds.
Understanding the structures of the SARS-CoV-2 viral proteins is essential to understanding its biology, its infectiousness, its transmissibility, and how to develop treatments for it. Our project focuses on enabling the process of structure determination for SARS-CoV-2 proteins.
The role of contaminated surfaces (fomites) in community transmission of SARS-CoV-2 has been debated. Our team is sampling high-touch public surfaces during the ongoing pandemic to improve understanding of the risk of SARS-CoV-2 infection when the public accesses essential businesses such as grocery stores, pharmacies, and gas stations.
Modeling COVID-19 in the context of optimizing quarantine policy using mobility patterns
We are designing a public health solution for contact tracing built around digital ecosystems. Our current focus is on improving privacy, user-experience, effectiveness, and adoption of digital contact tracing. With so many issues at forefront, the challenge to solve the contact tracing puzzle is manifold.
People’s ability to understand and personalize threats are key in getting them to adopt protective behaviors. COVID-19 presents a serious threat to health. However, unlike threats from other kinds of hazards, the virus does not offer any visible indication of its threat or presence.
We have a detailed transmission model that specifically focuses on the availability of testing strategies and their effect on the containment and spread of COVID-19, which is amenable to the systematic exploration of a wide range of important “what-if” scenarios.
The Northeast Big Data Hub is delighted to announce our Seed Fund program this month. Designed to promote collaboration in data science, the Seed Fund will encourage the cross-pollination of ideas, data and tools across disciplines and sectors including academia, industry, government, and communities. Funding provided through this program is intended […]
Guest post by Ivon Arroyo, Associate Professor in the College of Education and the College of Computer Science at the University of Massachusetts Amherst. The Big Data for Education Spoke’s professional development workshops have empowered teachers to leverage data to identify and answer a variety of pedagogical questions about their […]
Guest post by Ryan Baker, Associate Professor in the Graduate School of Education at the University of Pennsylvania. The Northeast Big Data for Education Spoke has conducted considerable outreach on methods for data science for educational data sets. Workshops have been conducted in New York City, Buffalo, Philadelphia, Pittsburgh, and […]
Guest post by Ryan Baker, Associate Professor in the Graduate School of Education at the University of Pennsylvania. The ASSISTments Longitudinal Data Competition invited data scientists around the world to participate in a competition around the analysis of student data. Data from middle school student use of a popular online […]
Data science is expanding rapidly in undergraduate education, but at the K-12 level, few schools have integrated this critical subject into their curricula. Many questions must be answered first: how should data science be taught to high schoolers? As a standalone course, or integrated throughout other courses? What level of […]
Studying the causes of disease is essential to medical research. However, the discussion is sometimes framed, misleadingly, as ‘nature vs. nurture’—is your condition the result of your genetics or your environment? Generally, the answer is both. But to what degree? A new study in Nature Genetics explores this question for […]
As part of our mission to address high-priority challenges with data-driven solutions, the Northeast Big Data Innovation Hub put out a call for workshop proposals this spring. We sought to support community-driven workshops that are designed to plan and develop Big Data projects, and are delighted to announce our first […]
We live in the age of the data deluge, with research group IDC forecasting that humankind will create and replicate 163 zettabytes of data by the year 2025. For perspective, only about 2.7 zettabytes were created and replicated globally in 2012. How might we most effectively manage our abundant data […]
Winning Schemes for Predicting Student Interest in Science UMass Amherst, WPI, Penn announce winners of Northeast big data competition AMHERST, Mass. – After a year-long, global data-mining competition, organizers today awarded the top three winning teams from Hong Kong, Japan and Michigan at the National Science Foundation’s (NSF) Northeast […]
With data touching all aspects of our lives today, how can we look beyond traditional approaches to data science education to build capacity as broadly and inclusively as possible? Leaders in data science education discussed “Alternative Avenues for Development of Data Science Education Capacity” on Friday, September 22nd, in a […]
Guest post by Catherine Cramer, NYSCI Increasingly, the prosperity, innovation and security of individuals and communities depend on a big data-literate society, which calls for a concerted effort to define what it means to be a big data literate citizen, information worker, researcher, or policymaker. As a step toward that […]
How can big data help predict student outcomes? Ryan Baker (U Penn) and Neil Heffernan (Worcester Polytechnic Institute) of our Big Data for Education Spoke hope to do just that via the Longitudinal Educational Big Data Competition. Using carefully de-identified, real-world educational data, participants will predict whether 172 students in validation and […]
Click here to access the report Data sharing challenges are extensive in cases involving industry and academia, and highlight the need for sharable, adaptable solutions. To that end, a report summarizing the proceedings and outputs of 2016’s Northeast Hub workshop on Data Sharing has recently been published. The workshop convened data science practitioners to […]
This post highlights one of the up-and-coming data science graduate students who participated in the Northeast Big Data Innovation Hub’s “Young Innovators” program this year. This program and others like it contribute to the Northeast Hub’s mission to build public-private partnerships to address high-priority societal challenges with data-driven solutions. The […]
The National Science Foundation (NSF) has published the Smart & Connected Communities (S&CC) program solicitation, spanning the Directorates for Computer and Information Science and Engineering (CISE); Education and Human Resources (EHR); Engineering (ENG); Geosciences (GEO); and Social, Behavioral and Economic Sciences (SBE). The goal of the S&CC program solicitation is […]
The Center for Discrete Mathematic and Theoretical Computer Science (DIMACS) at Rutgers University recently announced details of the planning grant it received from the National Science Foundation as part of the Big Data Hubs program. One of four planning grants (along with three full awards) issued to Northeast Big […]
On September 29th and 30th, stakeholders from across the Northeast and beyond joined the Hub at Drexel University in Philadelphia for “Enabling Seamless Data Sharing in Industry and Academia,” a cross-sector workshop put on by our community to tackle the challenges of sharing data head-on. In short “TED talk”-style presentations and […]
Click here for a PDF version of this release. Click here for the press release from the National Science Foundation (NSF). The National Science Foundation (NSF) has announced $3.3 million in grants to researchers affiliated with the Northeast Big Data Innovation Hub. A common theme underlying the projects below is […]
