Suvodeep Mazumdar, Stuart Wrigley and Fabio Ciravegna in Remote Sense: “The impact of Crowdsourcing and citizen science activities on academia, businesses, governance and society has been enormous. This is more prevalent today with citizens and communities collaborating with organizations, businesses and authorities to contribute in a variety of manners, starting from mere data providers to being key stakeholders in various decision-making processes. The “Crowdsourcing for observations from Satellites” project is a recently concluded study supported by demonstration projects funded by European Space Agency (ESA). The objective of the project was to investigate the different facets of how crowdsourcing and citizen science impact upon the validation, use and enhancement of Observations from Satellites (OS) products and services. This paper presents our findings in a stakeholder analysis activity involving participants who are experts in crowdsourcing, citizen science for Earth Observations. The activity identified three critical areas that needs attention by the community as well as provides suggestions to potentially help in addressing some of the challenges identified….(More)”.
Be the Change: Saving the World with Citizen Science
Book by It’s so easy to be overwhelmed by everything that is wrong in the world. In 2010, there were 660,000 deaths from malaria. Dire predictions about climate change suggest that sea levels could rise enough to submerge both Los Angeles and London by 2100. Bees are dying, not by the thousands but by the millions.
But what can you do? You’re just one person, right? The good news is that you *can* do something.
It’s called citizen science, and it’s a way for ordinary people like you and me to do real, honest-to-goodness, help-answer-the-big-questions science.
This book introduces you to a world in which it is possible to go on a wildlife survey in a national park, install software on your computer to search for a cure for cancer, have your smartphone log the sound pollution in your city, transcribe ancient Greek scrolls, or sift through the dirt from a site where a mastodon died 11,000 years ago—even if you never finished high school….(More)”
Crowdsourcing, Citizen Science, and Data-sharing
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)”
Esri, Waze Partnership: A Growing Trend in Sharing Data for the Benefit of All?
Justine Brown at GovTech: “Esri and Waze announced in mid-October that they’re partnering to help local governments alleviate traffic congestion and analyze congestion patterns. Called the Waze Connected Citizens Program, the program — which enables local governments that use the Esri ArcGIS platform to exchange publicly available traffic data with Waze — may represent a growing trend in which citizens and government share data for the benefit of all.
Connecting Esri and Waze data will allow cities to easily share information about the conditions of their roads with drivers, while drivers anonymously report accidents, potholes and other road condition information back to the cities. Local governments can then merge that data into their existing emergency dispatch and street maintenance systems….
Through the Connected Citizen program, Waze shares two main data sets with its government partners: Jams and Alerts….If there’s a major traffic jam in an unusual area, a traffic management center operator might be triggered to examine that area further. For example, Boston recently used Waze jam data to identify a couple of traffic-prone intersections in the Seaport district….Similarly if a Waze user reports a crash, that information shows up on the city’s existing ArcGIS map. City personnel can assess the crash and combine the Waze data with its existing data sets, if desired. The city can then notify emergency response, for example, to address the accident and send out emergency vehicles if necessary….
The Connected Citizen Program could also provide local governments an alternative to IoT investments, because a city can utilize real-time reports from the road rather than investing in sensors and IoT infrastructure. The Kentucky Transportation Cabinet, for instance, uses data from the Connected Citizen Program in several ways, including to monitor and detect automobile accidents on its roadways….(More)”
Digital Kenya: An Entrepreneurial Revolution in the Making
(Open Access) book edited by Bitange Ndemo and Tim Weiss: “Presenting rigorous and original research, this volume offers key insights into the historical, cultural, social, economic and political forces at play in the creation of world-class ICT innovations in Kenya. Following the arrival of fiber-optic cables in 2009, Digital Kenya examines why the initial entrepreneurial spirit and digital revolution has begun to falter despite support from motivated entrepreneurs, international investors, policy experts and others. Written by engaged scholars and professionals in the field, the book offers 15 eye-opening chapters and 14 one-on-one conversations with entrepreneurs and investors to ask why establishing ICT start-ups on a continental and global scale remains a challenge on the “Silicon Savannah”. The authors present evidence-based recommendations to help Kenya to continue producing globally impactful ICT innovations that improve the lives of those still waiting on the side-lines, and to inspire other nations to do the same….(More)”
Essays on collective intelligence
Thesis by Yiftach Nagar: “This dissertation consists of three essays that advance our understanding of collective-intelligence: how it works, how it can be used, and how it can be augmented. I combine theoretical and empirical work, spanning qualitative inquiry, lab experiments, and design, exploring how novel ways of organizing, enabled by advancements in information technology, can help us work better, innovate, and solve complex problems.
The first essay offers a collective sensemaking model to explain structurational processes in online communities. I draw upon Weick’s model of sensemaking as committed-interpretation, which I ground in a qualitative inquiry into Wikipedia’s policy discussion pages, in attempt to explain how structuration emerges as interpretations are negotiated, and then committed through conversation. I argue that the wiki environment provides conditions that help commitments form, strengthen and diffuse, and that this, in turn, helps explain trends of stabilization observed in previous research.
In the second essay, we characterize a class of semi-structured prediction problems, where patterns are difficult to discern, data are difficult to quantify, and changes occur unexpectedly. Making correct predictions under these conditions can be extremely difficult, and is often associated with high stakes. We argue that in these settings, combining predictions from humans and models can outperform predictions made by groups of people, or computers. In laboratory experiments, we combined human and machine predictions, and find the combined predictions more accurate and more robust than predictions made by groups of only people or only machines.
The third essay addresses a critical bottleneck in open-innovation systems: reviewing and selecting the best submissions, in settings where submissions are complex intellectual artifacts whose evaluation require expertise. To aid expert reviewers, we offer a computational approach we developed and tested using data from the Climate CoLab – a large citizen science platform. Our models approximate expert decisions about the submissions with high accuracy, and their use can save review labor, and accelerate the review process….(More)”
Open Innovation: Practices to Engage Citizens and Effectively Implement Federal Initiatives
United States Government Accountability Office: “Open innovation involves using various tools and approaches to harness the ideas, expertise, and resources of those outside an organization to address an issue or achieve specific goals. GAO found that federal agencies have frequently used five open innovation strategies to collaborate with citizens and external stakeholders, and encourage their participation in agency initiatives.
GAO identified seven practices that agencies can use to effectively implement initiatives that involve the use of these strategies:
- Select the strategy appropriate for the purpose of engaging the public and the agency’s capabilities.
- Clearly define specific goals and performance measures for the initiative.
- Identify and engage external stakeholders and potential partners.
- Develop plans for implementing the initiative and recruiting participants.
- Engage participants and partners while implementing the initiative.
- Collect and assess relevant data and report results.
- Sustain communities of interested partners and participants.
Aspects of these practices are illustrated by the 15 open innovation initiatives GAO reviewed at six selected agencies: the Departments of Energy, Health and Human Services, Housing and Urban Development, and Transportation (DOT); the Environmental Protection Agency; and the National Aeronautics and Space Administration (NASA).
For example:
• With the Asteroid Data Hunter challenge, NASA used a challenge and citizen science effort, beginning in 2014, to improve the accuracy of its asteroid detection program and develop an application for citizen scientists.
• Since 2009, DOT’s Federal Highway Administration has used an ideation initiative called Every Day Counts to identify innovations to improve highway project delivery. Teams of federal, state, local, and industry experts then implement the ideas chosen through this process….(More)”
How Technology is Crowd-Sourcing the Fight Against Hunger
Beth Noveck at Media Planet: “There is more than enough food produced to feed everyone alive today. Yet access to nutritious food is a challenge everywhere and depends on getting every citizen involved, not just large organizations. Technology is helping to democratize and distribute the job of tackling the problem of hunger in America and around the world.
Real-time research
One of the hardest problems is the difficulty of gaining real-time insight into food prices and shortages. Enter technology. We no longer have to rely on professional inspectors slowly collecting information face-to-face. The UN World Food Programme, which provides food assistance to 80 million people each year, together with Nielsen is conducting mobile phone surveys in 15 countries (with plans to expand to 30), asking people by voice and text about what they are eating. Formerly blank maps are now filled in with information provided quickly and directly by the most affected people, making it easy to prioritize the allocation of resources.
Technology helps the information flow in both directions, enabling those in need to reach out, but also to become more effective at helping themselves. The Indian Ministry of Agriculture, in collaboration with Reuters Market Light, provides information services in nine Indian languages to 1.4 million registered farmers in 50,000 villages across 17 Indian states via text and voice messages.
“In the United States, 40 percent of the food produced here is wasted, and yet 1 in 4 American children (and 1 in 6 adults) remain food insecure…”
Data to the people
New open data laws and policies that encourage more transparent publication of public information complement data collection and dissemination technologies such as phones and tablets. About 70 countries and hundreds of regions and cities have adopted open data policies, which guarantee that the information these public institutions collect be available for free use by the public. As a result, there are millions of open datasets now online on websites such as the Humanitarian Data Exchange, which hosts 4,000 datasets such as country-by-country stats on food prices and undernourishment around the world.
Companies are compiling and sharing data to combat food insecurity, too. Anyone can dig into the data on the Global Open Data for Agriculture and Nutrition platform, a data collaborative where 300 private and public partners are sharing information.
Importantly, this vast quantity of open data is available to anyone, not only to governments. As a result, large and small entrepreneurs are able to create new apps and programs to combat food insecurity, such as Plantwise, which uses government data to offer a knowledge bank and run “plant clinics” that help farmers lose less of what they grow to pests. Google uses open government data to show people the location of farmers markets near their homes.
Students, too, can learn to play a role. For the second summer in a row, the Governance Lab at New York University, in partnership with the United States Department of Agriculture (USDA), mounted a two-week open data summer camp for 40 middle and high school students. The next generation of problem solvers is learning new data science skills by working on food safety and other projects using USDA open data.
Enhancing connection
Ultimately, technology enables greater communication and collaboration among the public, social service organizations, restaurants, farmers and other food producers who must work together to avoid food crises. The European Food Safety Authority in Italy has begun exploring how to use internet-based collaboration (often called citizen science or crowdsourcing) to get more people involved in food and feed risk assessment.
In the United States, 40 percent of the food produced here is wasted, and yet 1 in 4 American children (and 1 in 6 adults) remain food insecure, according to the Rockefeller Foundation. Copia, a San Francisco based smartphone app facilitates donations and deliveries of those with excess food in six cities in the Bay Area. Zero Percent in Chicago similarly attacks the distribution problem by connecting restaurants to charities to donate their excess food. Full Harvest is a tech platform that facilitates the selling of surplus produce that otherwise would not have a market.
Mobilizing the world
Prize-backed challenges create the incentives for more people to collaborate online and get involved in the fight against hunger….(More)”
The Wisdom of the Crowd is what science really needs
Science/Disrupt: “In a world where technology allows for global collaboration, and in a time when we’re finally championing diversity of thought, there are few barriers to getting the right people together to work on some of our most pressing problems. Governments and research labs are attempting to apply this mentality to science through what is known as ‘Citizen Science’ – research conducted in part by the public (amateur scientists) in partnership with the professionals.
The concept of Citizen Science is brilliant: moving science forward, faster, by utilising the wisdom and volume of the crowd. …
But Citizen Science goes beyond working directly with people with specific data to share. Zooniverse – the home of Citizen Science online – lists hundreds of projects which anyone can get involved with to help advance science. From mapping the galaxy and looking for comets, to seeking outAustralian wildlife and helping computers understand animal faces, the projects span across many subjects.
But when you dig deeper into the tasks being asked of these CitizenScientists, you find that – really – it’s a simple data capture activity. There’s no skill involved other than engaging your eyes to see and fingers to click and type. It’s not the wisdom of the crowd which is being tapped into.
You could argue that people are interested purely in being a part of important research – which of course is true for many – but it misses the point that scientists are simply missing out on a great resource of intellect at their fingertips.
There has been a rise of crowdsourced solutions over the last few years. rLoopis an organisation formed over Reddit to propose a Hyperloop transportation capsule; Techfugees is a Global community of technologists who team up to propose and build solutions to problems facing the increasing numbers of refugees around the world; and XPRIZE is an open competition offering winning teams large sums of money and support to solve the global problems they select each year.
The difference between crowdsourcing and Citizen Science is that in the former, a high value is placed on ideas. There’s a general understanding that‘two minds are better than one’ and that by empowering a larger, more diverse pool of people to engage with important and purposeful work, a better solution will be found faster.
With Citizen Science, the mood is that of the public only being capable of playing hide and seek with pictures and completing menial, time consuming work that the scientists are simply too busy to do. …(More)”
Crowdsourcing: It Matters Who the Crowd Are
Paper by Alexis Comber, Peter Mooney, Ross S. Purves, Duccio Rocchini, and Ariane Walz: “Volunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under- and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors….(More)”