Corporate Banner
Satellite Banner
Scientific Community
Become a Member | Sign in
Home>News>This Article

Computational Center Will Study the Past and Future of Knowledge

Published: Monday, March 04, 2013
Last Updated: Monday, March 04, 2013
Bookmark and Share
Templeton Foundation awards $5.2 million for Computation Institute's Metaknowledge Network.

The march of science is stumbling and easily sidetracked, fraught with bias, fads and dead ends. A new research initiative based at the University of Chicago and the Computation Institute will use the latest computational tools to scrutinize this imperfect path and better understand how knowledge was and is created. Such understanding could transform the process of research, calling out past missteps while revealing unanticipated new directions for the future.

With a $5.2 million grant from the John Templeton Foundation, the new Metaknowledge Network brings together social scientists, computer scientists and domain experts from several disciplines to explore how knowledge emerges, thrives, evolves and dies out. The lessons learned can be used to accelerate discovery across fields, as scientists develop a deeper understanding of why we have the knowledge we have—and why certain promising questions were left unasked or unanswered.

“We have an opportunity to create a really rich science of science, one that builds on novel computational tools to exploit the increasingly widespread digital traces of the research process,” said James Evans, director of the center, associate professor of sociology, and Computation Institute Fellow.

Metaknowledge means “knowledge about knowledge”—the study of how different scientific questions and ideas appear, mature and potentially take root. The idealistic view of research is that it proceeds in unbiased, empirical steps. But scientists faced with an almost limitless number of potential questions may also choose a research path based on non-empirical factors such as available resources or equipment, professional and educational networks, access to previous findings and the biases and trends of their field.

Until now, the fingerprints of these external influences have been difficult to detect with the naked eye.

“Most of what we know comes from putting science under the microscope, from deep historical or ethnographic study,” said Jacob Foster, assistant professor of sociology and a member of the Metaknowledge Network.

But the current explosion of digitally available text, including journal publications, books, patents and news articles, makes it possible for the first time in history to study the dynamics that shape scientific research at scale, as the latest computational tools can capture some of the richness of these insights.

“The central idea is, how can we take these huge data resources associated with science today—all the publications, preprints and data that are floating around—and use that to figure out why people ask the questions that they ask?” Evans said. “And how can this knowledge lead us to ask better questions?”

Initial core projects within the Metaknowledge Network will examine why some theories are more popular than others, what strategies are most likely to produce groundbreaking research and how deeply held notions and assumptions shape what scientists study.

For example, preliminary work by network collaborators found that award-winning scientists were more likely to attempt riskier projects, which were subsequently cited more often by their peers. Other work identified biases in the production and analysis of data from many fields, and demonstrated how previous findings reported in the biomedical literature can distort how scientists interpret their own independent results, a kind of publication peer pressure.

In a time of tight research budgets, these insights can help direct funding to the most promising scholars and projects, rather than merely the most popular or prominent. A combination of text-mining and machine-learning tools also can potentially provide a continuously refreshed "sentinel" on a body of research, updating as new articles are published and suggesting new high-impact hypotheses to be explored.

“For science policy and the business of innovation, we could be much more rational about how we search through the enormous space of questions,” Evans said. “And that includes being more creative—asking new, unexpected questions.”

To support the network's research, a Knowledge Lab will be established at the Computation Institute on the UChicago campus for researchers to collaborate with computer programmers. The network also will build an online Metaknowledge Portal for sharing software, data and publications. Databases and results generated by the projects will be made open source and available to the public where legally possible.

The inaugural members of the Metaknowledge Network include researchers from the University of Chicago, Argonne National Laboratory, Stanford University, Northwestern University, the University of California, the University of Washington, the University of Wisconsin, Princeton University and Harvard University.

Further Information
Access to this exclusive content is for Technology Networks Premium members only.

Join Technology Networks Premium for free access to:

  • Exclusive articles
  • Presentations from international conferences
  • Over 2,800+ scientific posters on ePosters
  • More than 4,000+ scientific videos on LabTube
  • 35 community eNewsletters

Sign In

Forgotten your details? Click Here
If you are not a member you can join here

*Please note: By logging into you agree to accept the use of cookies. To find out more about the cookies we use and how to delete them, see our privacy policy.

Related Content

Gifts to Boost University of Chicago as Hub for Biomedical 'Big Data'
Two major gifts will build momentum behind the University of Chicago’s leadership in biomedical computation.
Thursday, April 18, 2013
Scientific News
Closing the Loop on an HIV Escape Mechanism
Research team finds that protein motions regulate virus infectivity.
World’s First Therapeutic Venom Database
Open-source library describes nearly 43,000 effects on the human body.
Mathematical Model Forecasts the Path of Breast Cancer
Chances of survival depend on which organs breast cancer tumors colonize first.
The Secret Behind the Power of Bacterial Sex
Migration between different communities of bacteria is the key to the type of gene transfer that can lead to the spread of traits such as antibiotic resistance, according to researchers at Oxford University.
Biomedical Imaging at One-Thousandth the Cost
Mathematical modeling enables $100 depth sensor to approximate the measurements of a $100,000 piece of lab equipment.
University of Glasgow Researchers Make An Impact in 60 Seconds
Early-career researchers were invited to submit an engaging, dynamic and compelling 60 second video illuminating an aspect of their research.
On Top of the Flu
Chance for advance warning in search-based tracking method.
TGAC Announces Milestone in Wheat Research
A more complete and accurate wheat genome assembly is being made available to researchers, by The Genome Analysis Centre (TGAC) on 12 November 2015.
Shedding Light on “Dark” Cellular Receptors
UNC and UCSF labs create a new research tool to find homes for two orphan cell-surface receptors, a crucial step toward finding better therapeutics and causes of drug side effects.
Is Allergy the Price We Pay for Our Immunity to Parasites?
New findings help demonstrate the evolutionary basis for allergy.
Scroll Up
Scroll Down

Skyscraper Banner
Go to LabTube
Go to eposters
Access to the latest scientific news
Exclusive articles
Upload and share your posters on ePosters
Latest presentations and webinars
View a library of 1,800+ scientific and medical posters
2,800+ scientific and medical posters
A library of 2,500+ scientific videos on LabTube
4,000+ scientific videos