Featured Projects

Rapid fabrication technologies, commonly known as “3D Printing,” enable the rapid creation of physical objects based on digital designs. Scanning technologies enable the opposing process, the creation of digital models derived from physical objects. This site provides information resources on 3D printing and scanning, and on library research projects regarding these technologies.

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The United States Census and the Program on Informatics at the Massachusetts Institute of Technology are convening a series of workshops to examine computational, social-scientific, statistical, and informatic challenges to building the next generation of official statistics. These workshops bring together select groups of experts in universities, industry, and the U.S. government to explore diverse approaches to engaging big data to inform a series of selected exemplar use cases faced by statistical agencies.

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Virtual learning environments are an increasingly important component of individualized learning in STEM domains. New technologies (including biometry and neuroimaging) provide new opportunities to unobtrusively measure student engagement and learning at scale. This project utilizes these technologies to provide foundational knowledge of the ways in which measures of implicit learning from lab settings, ubiquitous sensors, and big data might be linked to explicit learning to develop games and online educational systems that are adaptive to diverse learners.

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The drawing of electoral districts is among the least transparent processes in democratic governance. All too often, redistricting authorities maintain their power by obstructing public participation. The resulting districts embody the goals of politicians to the detriment of the representational interests of communities and the public at large. We have developed DistrictBuilder to increase participation and transparency in the electoral process.

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This project will help establish a formal linkage between scholarly publications and the underlying research data by integrating the OJS PKP and Harvard Dataverse Network systems.

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This project defines and measures privacy in mathematical and legal terms, and explores alternate definitions of privacy that may be more general or more practical. The research aims to provide a better understanding of the practical performance and usability of a variety of algorithms for analyzing and sharing privacy-sensitive data. The project will develop secure implementations of these algorithms and legal instruments, which will be made publicly available.

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Mission

The Program on Information Science seeks to solve emerging problems in information management that are essential to support new and innovative services, and to amplify the impact that MIT can have on the development of information science, information policy, and scholarly communication through participation in the development of standards, policy, and methods related to information science and information management.

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Latest News

Program Welcomes First Visiting Scholar - Philip Cohen, PhD.

Program Welcomes First Visiting Scholar - Philip Cohen, PhD.

October 3, 2018

The program is happy to welcome Dr. Philip Cohen to MIT for the Fall 2018 semester.  He is the first Visiting Scholar for the program and will be onsite here one week each in September, November, and January during IAP.  In November he will present a 1 hour talk which will be open to the public.  When not on site, Dr. Cohen will be at his home institution, the University of Maryland.  While here this semester his research will be focused on open peer review and the structure of publishing in the social sciences.

 

More about Dr. Cohen:...

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New article. Our framework for algorithmic fairness just published in a special issue on AI ethics

July 13, 2018

ABSTRACT

In this article, we recognize the profound effects that algorithmic decision making can have on people’s lives and propose a harm-reduction framework for algorithmic fairness. We argue that any evaluation of algorithmic fairness must take into account the foreseeable effects that algorithmic design, implementation, and use have on the well-being of individuals. We further demonstrate how counterfactual frameworks for causal inference developed in statistics and computer science can be used as the basis for defining and estimating the foreseeable...

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New Undergraduate Research Intern Joins the Program for Summer 2018

July 12, 2018

The program supports undergraduate and graduate internships, research affiliates, research assistants, and postdoctoral fellows. (For more information about internships see this page).

 

This summer the program is pleased to welcome Dylan Sam as a new Undergraduate Research Intern. 

 

Dylan is a research assistant and rising second year student at Brown University, currently...

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New Graduate Research Intern Joins the Program for Summer 2018

July 12, 2018

The program supports undergraduate and graduate internships, research affiliates, research assistants, and postdoctoral fellows. (For more information about internships see this page).

This summer the program is pleased to welcome Jessica Chapel as a new Graduate Research Intern. 

 

Jessica Chapel is a second-year student in the Simmons SLIS program focusing on digital libraries and archives...

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First UROP Joins Information Science Program for Spring 2018

First UROP Joins Information Science Program for Spring 2018

February 23, 2018

The program supports undergraduate and graduate internships, UROPS, research affiliates, research assistants, and postdoctoral fellows. (For more information about internships see this page).

This semester the program is pleased to welcome Sara Wilson as the first UROP of many to come.  Sara is sponsored through a joint program with the lab of...

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News from the community

Recent Publications

The Public Mapping ProjectHow Public Participation Can Revolutionize Redistricting
McDonald M, Altman M. The Public Mapping ProjectHow Public Participation Can Revolutionize Redistricting. Cornell University Press; 2018. Publisher's VersionAbstract

The Laurence and Lynne Brown Democracy Medal is an initiative of the McCourtney Institute for Democracy at Pennsylvania State University. It annually recognizes outstanding individuals, groups, and organizations that produce exceptional innovations to further democracy in the United States or around the world.

Micah Altman and Michael P. McDonald unveil the Public Mapping Project, which developed DistrictBuilder, an open-source software redistricting application designed to give the public transparent, accessible, and easy-to-use online mapping tools. As they show, the goal is for all citizens to have access to the same information that legislators use when drawing congressional maps—and use that data to create maps of their own.

Differential Privacy: A Primer for a Non-Technical Audience
Wood A, Altman M, Bembenek A, Bun M, Gaboardi M, Honaker J, O'Brien DR, Steinke T, Vadhan S. Differential Privacy: A Primer for a Non-Technical Audience. Vanderbilt Journal of Entertainment and Technology Law (JETlaw) [Internet]. 2018;21 :209-276. Publisher's VersionAbstract

ifferential privacy is a formal mathematical framework for quantifying and managing privacy risks. It provides provable privacy protection against a wide range of potential attacks, including those currently unforeseen. Differential privacy is primarily studied in the context of the collection, analysis, and release of aggregate statistics. These range from simple statistical estimations, such as averages, to machine learning. Tools for differentially private analysis are now in early stages of implementation and use across a variety of academic, industry, and government settings. Interest in the concept is growing among potential users of the tools, as well as within legal and policy communities, as it holds promise as a potential approach to satisfying legal requirements for privacy protection when handling personal information. In particular, differential privacy may be seen as a technical solution for analyzing and sharing data while protecting the privacy of individuals in accordance with existing legal or policy requirements for de-identification or disclosure limitation.

 

 

A Grand Challenges-Based Research Agenda for Scholarly Communication and Information Science
Altman M, Bourg C, Cohen P, Choudhury GS, Henry C, Kriegsman S, Minow M, Selematsela D, Sengupta A, Suber P, et al. A Grand Challenges-Based Research Agenda for Scholarly Communication and Information Science.; 2018. Publisher's VersionAbstract
The “Grand Challenges-Based Research Agenda for Scholarly Communication and Information Science” describes a vision for a more inclusive, open, equitable, and sustainable future for scholarship; characterizes the central technical, organizational, and institutional barriers to this future; describes the areas research needs to advance this future; and identifies targeted “grand challenge” research problems for knowledge generation. These “grand challenges” are fundamental research problems with broad applications, whose solutions are potentially achievable within the next decade.
Chassanoff A, Borghi J, AlNoamany Y, Thornton K. Software Curation in Research Libraries: Practice and Promise. he Journal of Librarianship and Scholarly Communication. 2018;Forthcoming.Abstract

INTRODUCTION. Research software plays an increasingly vital role in the scholarly record. Academic research libraries are in the early stages of exploring strategies for curating and preserving research software, aiming to provide long-term access and use. DESCRIPTION OF PROGRAM. In 2016, the Council on Library and Information Resources (CLIR) began offering postdoctoral fellowships in software curation. Four institutions hosted the initial cohort of software curation fellows. This article describes the work activities and research program of the cohort, highlighting the challenges and benefits of doing this exploratory work in research libraries. NEXT STEPS. Academic research libraries are poised to play an important role in research and development around robust services for software curation. The next cohort of CLIR fellows are set to begin in fall 2018 and will likely shape and contribute substantially to an emergent research agenda.

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