Emily Keller-O'Donnell, Journalist

DSSG Teams Present Their Final Project Results

Student fellows at the University of Washington Data Science for Social Good (DSSG) program presented the results of their 10-week summer projects on August 17th. The fellows conducted their work on four interdisciplinary teams, working with project leads and data scientists. 

Read the full article at eScience News here.

Interdisciplinary Team Designs Database to Advance ‘Self-Sufficiency Standard’ Research

Determining the income level that working families need to meet their basic needs requires a dynamic approach. An interdisciplinary team at the University of Washington (UW) Data Science for Social Good (DSSG) program is laying the groundwork for the integration of multi-sourced data from across the U.S. to provide researchers and policy makers with an expanded breadth of opportunities for analyzing complex information in new ways.

The project is centered on designing and testing a database for the Self-Sufficiency Standard, a project of the Center for Women’s Welfare at the UW School of Social Work that determines the income level required for working families to meet their minimum basic needs, based on family composition, children’s ages, and geographic differences in the cost of living. The Standard provides an alternative to the Official Poverty Measure that is currently used to calculate eligibility for benefits such as housing subsidies and food assistance across the U.S.

Read the full article at eScience News here.

Applying ‘Geospatial First’ Approach to Estimating Heating Loads in Alaska

Decarbonization efforts to mitigate the impacts of climate change face a unique challenge in Alaska. While about 70 percent of energy use in the state goes to heating, there is a lack of reliable broad-scale data on the portion of energy that is used for heating in buildings. An interdisciplinary team at the University of Washington Data Science for Social Good (DSSG) program is working to create an improved method for estimating thermal energy use in buildings in the Alaska Railbelt and Arctic regions, to support these efforts.

Read the full article at eScience News here.

OpenSidewalks Collaboration Wins METRO Innovative Solutions Award

A METRO Innovative Solutions Award was recently awarded to King County Metro (KCM) and MV Transportation for the development of CommonPaths, a new application that collects and integrates granular data about sidewalk and pathway conditions that influence pedestrian mobility, including for people with disabilities. The application can provide a basis for generating automated accessibility condition analysis, providing navigation instructions, and supporting transportation planning and research.

Read the full article at the Cascadia Urban Analytics Cooperative website here.

Data Science for Social Good Fellows Present Their Project Results

This year, two interdisciplinary teams at the eScience Institute’s Data Science for Social Good (DSSG) program tackled timely issues, conducting projects to identify disinformation articles about the coronavirus and detect minority vote dilution resulting from geographic boundary setting in state, city, county and school board districts.

On August 19th, the DSSG student fellows presented the results of their projects, conducted with project leads and data scientists, to more than 130 people via zoom.  The ten-week summer program joins student fellows from universities around the country with data and domain researchers, and real-world stakeholders, to work on collaborative projects for societal benefit. This year the program took place remotely for the first time due to the coronavirus pandemic.

Read the full article at eScience News here.

Guidance for Responsible Big Data Research

“Ten simple rules for responsible big data research,” published in PLoS Computational Biology, provides practical guidance for big data researchers on the complexities of privacy protections, preventing re-identification of research subjects, and recognizing the difference between publicly available data and user consent for third-party research. This paper represents the work of the Council for Big Data, Ethics, and Society, funded by the National Science Foundation grant # IIS-1413864.

Authors: Matthew Zook, Solon Barocas, danah boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, and Frank Pasquale, March 30, 2017.

Read the paper here.

Supporting Ethics in Data Research

University campuses provide an ecosystem of support to technical researchers, including computer scientists, as they navigate emerging issues of privacy, ethics, security, and consent in big data research. These support systems have varying levels of coordination and may be implicit or explicit.

As part of the Supporting Ethics in Data Research project at Data & Society, we held workshops with twelve to sixteen student researchers, professors, information technology leaders, repository managers, and research librarians at a handful of universities. The goal was to tease out the individual components of ethical, technical, and legal support that were available or absent on each campus, and to better understand the interactions between different actors as they encounter common ethical quandaries.

Read the final report.

Devices, Data, Waste

When Basel Action Network (BAN), an electronic waste watchdog organization in Washington, implicated Total Reclaim — a purportedly reliable waste company — in a trash tracking investigation for covertly shipping LCD monitors overseas, it illustrated the complexities of pursuing environmental responsibility amidst the growth of online computing.

In a recent apology statement issued in response to BAN’s discovery of two mercury-containing monitors at an undocumented facility in Hong Kong, Total Reclaim cited business pressures such as a drop in commodity prices and increasing labor costs, and emphasized the “dramatically increasing volume of flat-screen devices” as contributing factors to its “ethical lapses.”

The study found that nearly one-third of 200 tracked devices had been sent overseas by multiple companies, including Dell Reconnect, a partnership with Goodwill. As a result of the investigation, the e-Stewards program, which counts Total Reclaim as a founding member, has revoked its certification for two years, while citing a “broken” economic and regulatory system that fails to provide “a sustainable and ethical electronics recycling infrastructure.”

This comes as device ownership and data creation are growing substantially. The Pew Research Center found that 36% of Americans owned three devices — a smartphone, computer, and tablet — in 2015, compared with 15% in 2012. This proliferation of devices has caused toxic impacts at unregulated overseas facilities, far outside the purview of customers.

Prior to disposal, their use is generating a secondary environmental footprint via WiFi and mobile Internet use, drawing on natural resources to power a sprawling network of cloud data centers that support increasing storage, sharing, and streaming.

Read the full article on Data & Society: Points.

Perspectives on Big Data, Ethics, and Society

With Jacob Metcalf and danah boyd, prepared comprehensive white paper outlining the findings of the Council for Big Data, Ethics, and Society hosted by Data & Society Research Institute and funded by the National Science Foundation. This paper discusses the disconnect between traditional ethics regulations and emerging big data research, providing recommendations for policy and pedagogical interventions to incorporate current ethics issues into industry practice and academia. Read the white paper.

Big Data Ethics Support Systems and Networks

A presentation by Emily F. Keller and Bonnie Tijerina on the Supporting Ethics in Data Research project at Data & Society Research Institute, which explores the current and potential partnerships between computer science researchers, librarians, and support systems on campus to address emerging ethical issues in the research process.