Data Analysis

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Universal Access to Knowledge

To harness advances in digital information technology to facilitate the openness and accessibility of all knowledge in the digital age for the widest public benefit under fair and secure conditions.

Scholarly Communication

To empower researchers by supporting the development and adoption of new resources for managing the increasingly diverse array of digital communication channels, enabling scientists to more effectively locate relevant research, network with other researchers, and disseminate their work to the scientific community and the public.

Data & Computational Research

To accelerate scientific discovery by helping researchers fully exploit the opportunities created by recent advances in our ability to collect, transmit, analyze, store, and manipulate data.

Institute for Research on Innovation and Science (IRIS) Awards

The Institute for Research on Innovation and Science (IRIS) seeks to fund researchers who will use the IRIS data to address questions about the social and economic returns to investments in research. IRIS seeks to enable fundamental research on the results of public and private investments that support discovery, innovation, and education on the campuses of U.S. universities.

Deadline: 

Monday, October 1, 2018

RIDIR: Collaborative Research: Computational and Historical Resources on Nations and Organizations for the Social Sciences (CHRONOS)

This project will collect, process, and analyze millions of U.S. government records concerning international relations, develop tools to explore these records, and make all of them available on a single website with an Application Programming Interface. The project will demonstrate how computational techniques can aid both qualitative and quantitative social science research on a range of areas of major public interest, expanding knowledge about terrorism, intelligence, international trade and aid.

Doctoral Dissertation Research in Science of Science and Innovation Policy: From Cycles to Spirals: Structural Analysis of Scientific Consensus Formation

The project develops a new strategy to explain and measure scientific consensus formation. It develops a quantitative measure of scientific consensus, based on an analysis of the structure of scientific citation networks. The measure is validated by exploiting changing consensus levels across time regarding several scientific propositions, such as "smoking causes cancer", "Human activity causes a climate change", etc.

Summer Fellowships

To support summer residential fellowships at one of Mathematica's offices doing independent research.

Deadline: 

Friday, February 16, 2018
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