PEOPLE

Crowdsourcing Medical Data Through Gaming

Curated on January 17, 2017August 3, 2018 by Stefaan Verhulst

Felix Morgan in The Austin Chronicle: “Video games have changed the way we play, but they also have the potential to change the way we research and solve problems, in fields such as health care and education. One game that’s made waves in medical research is Sea Hero Quest. This smartphone game has created a groundbreaking approach to data collection, leading to an earlier diagnosis of dementia. So far, 2.5 million people have played the game, providing scientists with years’ worth of data across borders and demographics.

By offering this game as a free mobile app, researchers are overcoming the ever-present problems of small sample sizes and time-consuming data gathering in empirical research. Sea Hero Quest was created by Glitchers, partnering with University College London, University of East Anglia, and Alzheimer’s Research. As players navigate mazes, shoot flares into baskets, and photograph sea creatures, they answer simple demographic questions and generate rich data sets.

“The idea of crowdsourced data-gathering games for research is a new and exciting method of obtaining data that would be prohibitively expensive otherwise,” says Paul Toprac, who along with his colleague Matt O’Hair, run the Simulation and Game Applications (SAGA) Lab at University of Texas Austin. Their team helps researchers across campus and in the private sector design, implement, and find funding for video game-based research.

O’Hair sees a lot of potential for Sea Hero Quest and other research-based games. “One of the greatest parts about the SAGA Lab is that we get to help researchers make strides in these kinds of fields,” he says.

The idea of using crowdsourcing for data collection is relatively new, but using gaming for research is something that has been well established. Last year at SXSW, Nolan Bushnell, the founder of Atari, made a statement that video games were the key to understanding and treating dementia and related issues, which certainly seems possible based on the preliminary results from Sea Hero Quest. “We have had about 35 years of research using games as a medium,” Toprac says. “However, only recently have we used games as a tool for explicit data gathering.”…(More)”

Fighting Ebola with information

Curated on January 13, 2017October 24, 2018 by Stefaan Verhulst

Larissa Fast and Adele Waugaman at Global Innovation Exchange: What can be learned from the use of data, information, and digital technologies, such as mobile-based systems and internet connectivity, during the Ebola outbreak response in West Africa? What worked, what didn’t, and how can we apply these lessons to improve data and information flows in the future? This report details key findings and recommendations about the collection, management, analysis, and use of paper-based and digital data and information, drawing upon the insights of more than 130 individuals and organizations who worked tirelessly to end the Ebola outbreak in West Africa in 2014 and 2015….(More)”

Governing with Collective Intelligence

Curated on January 12, 2017August 3, 2018 by Stefaan Verhulst

Tom Saunders and Geoff Mulgan at Nesta: “This paper provides an introduction to collective intelligence in government. It aims to be useful and relevant to governments of countries at very different levels of development. It highlights the ways in which governments are better understanding the world around them, drawing on ideas and expertise from their citizens, and encouraging greater scrutiny of their actions.

Collective intelligence is a new term to describe something which is in some respects old, but in other respects changing dramatically thanks to advances in digital technologies. It refers to the ability of large groups – a community, region, city or nation – to think and act intelligently in a way that amounts to more than the sum of their parts.

Key findings

Our analysis of government use of collective intelligence initiatives around the world finds that activities fall into four broad categories:

1. Better understanding facts and experiences: using new digital tools to gather data from many more sources.

2. Better development of options and ideas: tapping into the collective brainpower of citizens to come up with better ideas and options for action.

3. Better, more inclusive decision-making: involving citizens in decision making, from policymaking to planning and budgeting.

4. Better oversight of what is done: encouraging broader involvement in the oversight of government activity, from monitoring corruption to scrutinising budgets, helping to increase accountability and transparency….(More)”

Crowdsourcing, Citizen Science, and Data-sharing

Curated on January 11, 2017August 3, 2018 by Stefaan Verhulst

Sapien Labs: “The future of human neuroscience lies in crowdsourcing, citizen science and data sharing but it is not without its minefields.

A recent Scientific American article by Daniel Goodwin, “Why Neuroscience Needs Hackers,” makes the case that neuroscience, like many fields today, is drowning in data, begging for application of advances in computer science like machine learning. Neuroscientists are able to gather realms of neural data, but often without big data mechanisms and frameworks to synthesize them.

The SA article describes the work of Sebastian Seung, a Princeton neuroscientist, who recently mapped the neural connections of the human retina from an “overwhelming mass” of electron microscopy data using state of the art A.I. and massive crowd-sourcing. Seung incorporated the A.I. into a game called “Eyewire” where 1,000s of volunteers scored points while improving the neural map. Although the article’s title emphasizes advanced A.I., Dr. Seung’s experiment points even more to crowdsourcing and open science, avenues for improving research that have suddenly become easy and powerful with today’s internet. Eyewire perhaps epitomizes successful crowdsourcing — using an application that gathers, represents, and analyzes data uniformly according to researchers’ needs.

Crowdsourcing is seductive in its potential but risky for those who aren’t sure how to control it to get what they want. For researchers who don’t want to become hackers themselves, trying to turn the diversity of data produced by a crowd into conclusive results might seem too much of a headache to make it worthwhile. This is probably why the SA article title says we need hackers. The crowd is there but using it depends on innovative software engineering. A lot of researchers could really use software designed to flexibly support a diversity of crowdsourcing, some AI to enable things like crowd validation and big data tools.

The Potential

The SA article also points to Open BCI (brain-computer interface), mentioned here in other posts, as an example of how traditional divisions between institutional and amateur (or “citizen”) science are now crumbling; Open BCI is a community of professional and citizen scientists doing principled research with cheap, portable EEG-headsets producing professional research quality data. In communities of “neuro-hackers,” like NeurotechX, professional researchers, entrepreneurs, and citizen scientists are coming together to develop all kinds of applications, such as “telepathic” machine control, prostheses, and art. Other companies, like Neurosky sell EEG headsets and biosensors for bio-/neuro-feedback training and health-monitoring at consumer affordable pricing. (Read more in Citizen Science and EEG)

Tan Le, whose company Emotiv Lifesciences, also produces portable EEG head-sets, says, in an article in National Geographic, that neuroscience needs “as much data as possible on as many brains as possible” to advance diagnosis of conditions such as epilepsy and Alzheimer’s. Human neuroscience studies have typically consisted of 20 to 50 participants, an incredibly small sampling of a 7 billion strong humanity. For a single lab to collect larger datasets is difficult but with diverse populations across the planet real understanding may require data not even from thousands of brains but millions. With cheap mobile EEG-headsets, open-source software, and online collaboration, the potential for anyone can participate in such data collection is immense; the potential for crowdsourcing unprecedented. There are, however, significant hurdles to overcome….(More)”

Public Sector Entrepreneurship and the Integration of Innovative Business Models

Curated on January 10, 2017August 3, 2018 by Stefaan Verhulst

Book edited by Mateusz Lewandowski and Barbara Kożuch: “While private, for-profit businesses have typically been the most experienced with entrepreneurship, the study of public sector business models is coming to the forefront of entrepreneurial discussions. This shift has allowed researchers and practitioners to expand on their knowledge of positive business choices and paved the way for more profitable business empires.

Public Sector Entrepreneurship and the Integration of Innovative Business Models is a comprehensive source of academic research that discusses the latest entrepreneurial strategies, achievements, and challenges in public sector contexts. Highlighting relevant topics such as public management, crowdsourcing, municipal cooperation, and public sector marketing, this is an ideal resource for managers, practitioners, researchers, and professionals interested in learning more about public sector business ideals, and how these models are shaping positive entrepreneurial communities around the world….(More)”

Montreal monitoring city traffic via drivers’ Bluetooth

Curated on January 4, 2017August 3, 2018 by Stefaan Verhulst

Springwise: “Rather than rely on once-yearly spot checks of traffic throughout the city, Montreal, Canada, decided to build a more comprehensive picture of what was working well, and what wasn’t working very well, around the city. Working with traffic management company Orange Traffic, the city installed more than 100 sensors along the busiest vehicular routes. The sensors pick up mobile phone Bluetooth signals, making the system inexpensive to use and install as no additional hardware or devices are needed.

Once the sensors pick up a Bluetooth signal, they track it through several measurement points to get an idea of how fast or slow traffic is moving. The data is sent to the city’s Urban Mobility Management Center. City officials are keen to emphasize that no personal data is recorded as Bluetooth signals cannot be linked to individuals. Traffic management and urban planning teams will be able to use the data to redesign problematic intersections and improve the overall mobility of the city’s streets and transport facilities.

Smart cities are those making safety and efficiency a priority, from providing digital driver licenses in India to crowdsourcing a map of cars in bike lanes in New York City….(More)”

Pushing the Limits of Collective Intelligence

Curated on December 23, 2016August 3, 2018 by Stefaan Verhulst

Stanford Innovation Lab Podcast with Tina Seelig:

“Imagine a collective brain shaped by human insights and powered by technology – that’s crowdsourcing. Michael Bernstein, computer scientist at Stanford University, explores how to harness crowdsourcing to tackle daunting challenges. In this episode of Stanford Innovation Lab, Tina Seelig meets with Michael to discuss examples of successful crowdsourcing, tools to gather collective insights, and the evolving relationship between humans and machines….(More)”

Can you crowdsource water quality data?

Curated on December 16, 2016May 29, 2019 by Stefaan Verhulst

Pratibha Mistry at The Water Blog (Worldbank): “The recently released Contextual Framework for Crowdsourcing Water Quality Data lays out a strategy for citizen engagement in decentralized water quality monitoring, enabled by the “mobile revolution.”

According to the WHO, 1.8 billion people lack access to safe drinking water worldwide. Poor source water quality, non-existent or insufficient treatment, and defects in water distribution systems and storage mean these consumers use water that often doesn’t meet the WHO’s Guidelines for Drinking Water Quality.

The crowdsourcing framework develops a strategy to engage citizens in measuring and learning about the quality of their own drinking water. Through their participation, citizens provide utilities and water supply agencies with cost-effective water quality data in near-real time. Following a typical crowdsourcing model: consumers use their mobile phones to report water quality information to a central service. That service receives the information, then repackages and shares it via mobile phone messages, websites, dashboards, and social media. Individual citizens can thus be educated about their water quality, and water management agencies and other stakeholders can use the data to improve water management; it’s a win-win.

*A well-implemented crowdsourcing project both depends on and benefits end users.*Source: Figure modified from Hutchings, M., Dev, A., Palaniappan, M., Srinivasan, V., Ramanathan, N., Taylor, J. 2012. “mWASH: Mobile Phone Applications for the Water, Sanitation, and Hygiene Sector.” Pacific Institute, Oakland, California. 114 p. (*Link to full text*)

Several groups, from the private sector to academia to non-profits, have taken a recent interest in developing a variety of so-called mWASH apps (mobile phone applications for the water, sanitation, and hygiene WASH sector). A recent academic study analyzed how mobile phones might facilitate the flow of water quality data between water suppliers and public health agencies in Africa. USAID has invested in piloting a mobile application in Tanzania to help consumers test their water for E. coli….(More)”

Arcep goes forward with crowdsourcing data for regulation in France

Curated on December 12, 2016May 29, 2019 by Stefaan Verhulst

IIC: “France’s regulator, Arcep, says it is taking another step towards crowdsourcing to reflect users’ experience as accurately as possible, as part of a data-centric approach to regulation. It says it has decided to bring changes to its scoreboards on network and service coverage and quality, to provide users with more reliable and more representative measurements of fixed internet access and telephone services. To this end, it intends to make use of new digital tools that will enable any user to obtain a reliable, objective and reproducible measurement of how their individual access is performing. Crowdsourcing instruments will also allow Arcep to obtain a wealth of collaboratively produced information, which will help in identifying any market failures.

The objective over time: to reflect the user experience as accurately as possible, as part of a data-centric approach to regulation. “The aim of making information transparent is to allow citizen-consumers to steer the market”. To be able to commit fully to this new approach, an adjustment must be made to the current regulatory framework, and Arcep has launched a public consultation on a draft decision, amending the framework decision of 2013 on measuring and publishing fixed service QoS indicators. In particular, provisions regarding the quality of fixed internet access and telephone services, which have become superfluous, will be removed starting in the second half of 2017….(More)”