science

Crowd diagnosis could spot rare diseases doctors miss

Curated on April 22, 2013November 13, 2018 by Stefaan Verhulst

New Scientist: “Diagnosing rare illnesses could get easier, thanks to new web-based tools that pool information from a wide variety of sources…CrowdMed, launched on 16 April at the TedMed conference in Washington DC, uses crowds to solve tough medical cases.

Anyone can join CrowdMed and analyse cases, regardless of their background or training. Participants are given points that they can then use to bet on the correct diagnosis from lists of suggestions. This creates a prediction market, with diagnoses falling and rising in value based on their popularity, like stocks in a stock market. Algorithms then calculate the probability that each diagnosis will be correct. In 20 initial test cases, around 700 participants identified each of the mystery diseases as one of their top three suggestions….

Frustrated patients and doctors can also turn to FindZebra, a recently launched search engine for rare diseases. It lets users search an index of rare disease databases looked after by a team of researchers. In initial trials, FindZebra returned more helpful results than Google on searches within this same dataset.”

White House: Unleashing the Power of Big Data

Curated on April 21, 2013August 3, 2018 by Stefaan Verhulst

Tom Kalil, Deputy Director for Technology and Innovation at OSTP : “As we enter the second year of the Big Data Initiative, the Obama Administration is encouraging multiple stakeholders, including federal agencies, private industry, academia, state and local government, non-profits, and foundations to develop and participate in Big Data initiatives across the country. Of particular interest are partnerships designed to advance core Big Data technologies; harness the power of Big Data to advance national goals such as economic growth, education, health, and clean energy; use competitions and challenges; and foster regional innovation.
The National Science Foundation has issued a request for information encouraging stakeholders to identify Big Data projects they would be willing to support to achieve these goals. And, later this year, OSTP, NSF, and other partner agencies in the Networking and Information Technology R&D (NITRD) program plan to convene an event that highlights high-impact collaborations and identifies areas for expanded collaboration between the public and private sectors.”

Work-force Science and Big Data

Curated on April 21, 2013August 3, 2018 by Stefaan Verhulst

Steve Lohr from the New York Times: “Work-force science, in short, is what happens when Big Data meets H.R….Today, every e-mail, instant message, phone call, line of written code and mouse-click leaves a digital signal. These patterns can now be inexpensively collected and mined for insights into how people work and communicate, potentially opening doors to more efficiency and innovation within companies.

Digital technology also makes it possible to conduct and aggregate personality-based assessments, often using online quizzes or games, in far greater detail and numbers than ever before. In the past, studies of worker behavior were typically based on observing a few hundred people at most. Today, studies can include thousands or hundreds of thousands of workers, an exponential leap ahead.

“The heart of science is measurement,” says Erik Brynjolfsson, director of the Center for Digital Business at the Sloan School of Management at M.I.T. “We’re seeing a revolution in measurement, and it will revolutionize organizational economics and personnel economics.”

The data-gathering technology, to be sure, raises questions about the limits of worker surveillance. “The larger problem here is that all these workplace metrics are being collected when you as a worker are essentially behind a one-way mirror,” says Marc Rotenberg, executive director of the Electronic Privacy Information Center, an advocacy group. “You don’t know what data is being collected and how it is used.”

Interpretative Communities

Curated on April 14, 2013December 7, 2022 by Stefaan Verhulst

Communities to sense locally of open government data.

A new paper on “Local governance in the new information ecology” in the journal Public Money & Management calls for the creation of “interpretative communities” to make sense locally of open government data. In particular, they argue that:

“The availability of this open government data… solves nothing: as many writers have pointed out, such data needs to be interpreted and interpretation is always a function of a collective—what has been called an ‘interpretative’ or ‘epistemic’ community.”

The call mirrors the emerging view that the next stage regarding open data is to focus on making sense of the data and using it to serve the public good.

The authors identify “three different models of ‘interpretative communities’ that have emerged over the last few decades, drawing on, respectively, literary theory, science and technology studies and international politics”—including reference groups, epistemic communities, and expert networks. As to developing these communities locally, the paper states that it will require us…

“to rethink the resources and institutions that could support a local use of OGD and other resources. Such institutional support for local interpretation cannot be wholly local but needs to draw, in a critical and interactive manner, on wider knowledge bases. In the end, the model of the local that needs to be mobilized is not one based on spatial propinquity alone, or on a bounded sense of local, but one in which the local is seen as relational, connected and dynamic…we might look to the new technologies, and the newly-emerged social networks or Web 2.0 in particular, for such a balance of the local and the extra local”.

The paper ultimately is a critique of the current movement to provide open data that is presented as objective knowledge but is based on a “view from nowhere”…

“To make it into the view from somewhere will require the construction of powerful, yet open, interpretative communities to enact local governance with all of the subsequent questions arising about current modes of democratic representation, sectional interests in the third and private sector and centrallocal government dynamics. The prospects of such an information ecology to support interpretative community building emerging in the current environment in anything other than a piecemeal and reactive way do not appear promising.”

Data Science: The Numbers of Our Lives

Curated on April 12, 2013August 15, 2018 by Stefaan Verhulst

NYT on the integration of data science within universities: “In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates.”

The Science of What We Do (and Don't) Know About Data Visualization

Curated on April 12, 2013August 3, 2018 by Stefaan Verhulst

Robert Kosara on the HBR Blog Network: “Visualization is easy, right? After all, it’s just some colorful shapes and a few text labels. But things are more complex than they seem, largely due to the the ways we see and digest charts, graphs, and other data-driven images. While scientifically-backed studies do exist, there are actually many things we don’t know about how and why visualization works. To help you make better decisions when visualizing your data, here’s a brief tour of the research.”

June 1: National Day of Civic Hacking

Curated on April 11, 2013November 13, 2018 by Stefaan Verhulst

From Peter Welsch at the White House: “On the first weekend in June, civic activists, technology experts, and entrepreneurs around the country will gather together for the National Day of Civic Hacking. By combining their expertise with new technologies and publicly released data, participants hope to build tools that help others in their own neighborhoods and across the United States”.

Apply for the National Day of Civic Hacking at the White House. The deadline for applications is 5:00pm on Friday, April 19.