How and When to Involve Crowds in Scientific Research - The Book

How and When to Involve Crowds in Scientific Research | James Evans

The lone academic in a basement lab is an endangered species. Years ago I asked Paul Ginsparg, who founded arXiv, what features his machine-learning filter used to flag speculative submissions. The top three: single-authored, submitted on a weekend, and heavy citation of Newton and Einstein. Science is a contact sport now. Marion Poetz and Henry Sauermann's How and When to Involve Crowds in Scientific Research (https://lnkd.in/g5pwVbfD) is the field manual. What crowds can do: Volume. Zooniverse mobilizes 2.7 million people to classify galaxies and court records. Galaxy Zoo's co-founder hand-classified 50,000 galaxies in one week before concluding that isolation would break him. Reach. NASA spent years failing to predict solar flares, then broadcast the problem. The winner was a semi-retired radio engineer in rural New Hampshire who swapped satellite data for radio data. Experience. Patients and caregivers asked to generate research questions produced 826 that scientists had missed, including the link between aging and wound healing. Bench-to-bedside runs backward. One caution the book underplays: an open call is not an inclusive one. Participation costs in time, money, and access screen people out. Self-selection can narrow the very diversity that makes crowds thrive. As AI floods the labor supply of routine, homogeneous cognition, human crowds become more valuable, not less. Machines process. People notice what nobody thought to ask. Check out my review @ https://lnkd.in/gkzvWrRC and the book @ https://lnkd.in/g5pwVbfD!

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Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Request PDF

Request PDF | On Jan 1, 2013, Jessica McCallum Breen and others published Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Find, read and cite all the research you need on ResearchGate

Science as Collective Sensemaking

What is Science?

Science as Collective Sensemaking

What is Science?

Managing scientific knowledge for policy on the ATmosphere - Mathew's newsletter

Two types of Atmosphere toolkit are needed if ATScience is to help scientists do science and better communicate it to other audiences: one serving the researchers and their teams, the other focused on aggregation and synthesis.

Crowdsourced Health Research Studies: An Important Emerging Complement to Clinical Trials in the Public Health Research Ecosystem

Background: Crowdsourced health research studies are the nexus of three contemporary trends: 1) citizen science (non-professionally trained individuals conducting science-related activities); 2) crowdsourcing (use of web-based technologies to recruit project participants); and 3) medicine 2.0 / health 2.0 (active participation of individuals in their health care particularly using web 2.0 technologies). Crowdsourced health research studies have arisen as a natural extension of the activities of health social networks (online health interest communities), and can be researcher-organized or participant-organized. In the last few years, professional researchers have been crowdsourcing cohorts from health social networks for the conduct of traditional studies. Participants have also begun to organize their own research studies through health social networks and health collaboration communities created especially for the purpose of self-experimentation and the investigation of health-related concerns. Objective: The objective of this analysis is to undertake a comprehensive narrative review of crowdsourced health research studies. This review will assess the status, impact, and prospects of crowdsourced health research studies. Methods: Crowdsourced health research studies were identified through a search of literature published from 2000 to 2011 and informal interviews conducted 2008-2011. Keyword terms related to crowdsourcing were sought in Medline/PubMed. Papers that presented results from human health studies that included crowdsourced populations were selected for inclusion. Crowdsourced health research studies not published in the scientific literature were identified by attending industry conferences and events, interviewing attendees, and reviewing related websites. Results: Participatory health is a growing area with individuals using health social networks, crowdsourced studies, smartphone health applications, and personal health records to achieve positive outcomes for a variety of health conditions. PatientsLikeMe and 23andMe are the leading operators of researcher-organized, crowdsourced health research studies. These operators have published findings in the areas of disease research, drug response, user experience in crowdsourced studies, and genetic association. Quantified Self, Genomera, and DIYgenomics are communities of participant-organized health research studies where individuals conduct self-experimentation and group studies. Crowdsourced health research studies have a diversity of intended outcomes and levels of scientific rigor. Conclusions: Participatory health initiatives are becoming part of the public health ecosystem and their rapid growth is facilitated by Internet and social networking influences. Large-scale parameter-stratified cohorts have potential to facilitate a next-generation understanding of disease and drug response. Not only is the large size of crowdsourced cohorts an asset to medical discovery, too is the near-immediate speed at which medical findings might be tested and applied. Participatory health initiatives are expanding the scope of medicine from a traditional focus on disease cure to a personalized preventive approach. Crowdsourced health research studies are a promising complement and extension to traditional clinical trials as a model for the conduct of health research.

The Engine of Scientific Discovery: How New Methods and Tools Spark Major Breakthroughs

Abstract. How do we spark new scientific discoveries? Why do some breakthroughs seem even accidental? And most importantly, how can we accelerate them and

Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

AI has supercharged scientists—but may have shrunk science

Analysis of 41 million papers finds that although AI expands individual impact, it narrows collective scientific exploration

Nova Scotia’s Experiment in Research That Solves Real Problems

Locally focused research investments enable coalitions of scientists and citizens to serve community needs.

Nova Scotia’s Experiment in Research That Solves Real Problems

Locally focused research investments enable coalitions of scientists and citizens to serve community needs.

The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

Sir Isaac Newton famously wrote, “If I have seen further, it is by standing on the shoulders of giants”. Scientific contributions are rarely developed in isolation, but build upon prior contributions, such as problem framings, experimental methods, and empirical findings. Understanding these prerequisite relationships is important for studying scientific progress, and for automated scientific discovery systems that must reason about which existing capabilities can be used to develop new ones (e.g. Lu et al., 2024; Jansen et al., 2025b; Baek et al., 2025).