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The Mimir Project

Venn diagram with intersecting circles of process, creativity, and innovation. The overlapping area is labeled ideas

Image courtesy of Stuart Miles at FreeDigitalPhotos.net

 What drives the dynamics of science?

Governments, companies, and academic organizations regularly try to speed scientific progress in key areas by forming interdisciplinary centers. Do these innovations or recombinations accelerate research or decelerate it by moving scientists away from their disciplinary contexts? Are interdisciplinary confluences already underway when these centers are created, or do they induce new synergies among researchers? What kinds of organizational models most effectively promote interdisciplinary research?

About the project

The research team has embarked on a longitudinal study of how scientific ideas, scholarly networks, and their institutional contexts influence one another. This project will take advantage of special access to data about Stanford University and its $4.3 billion dollar funding drive (commenced in 1998), which attempts to bolster interdisciplinary centers and alter university research so it addresses real world problems. This data will be set against the backdrop of large scale public data sources.  The project aims to develop evidence-based tools and visualizations that reveal whether and how the form and content of intellectual work is changing in response to these major initiatives.

Goals

Our interdisciplinary team will apply new computational techniques in order to:

  • study the spread of ideas and methods across disciplines
  • contrast the success of virtual and ephemeral versus formal and physical organizations
  • understand the complex behavior of a large-scale intellectual enterprise and what attributes are important for successful innovation

Faculty Directors

The project is directed by the following Stanford faculty members:

  • Daniel Jurafsky
  • Christopher Manning
  • Dan McFarland
  • Woody Powell

Learn more

For details on this project, including a list of researchers and current findings, visit the Stanford Natural Language Processing Group page.