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Reinventing Discovery

Reinventing Discovery

The New Era of Networked Science
by Michael Nielsen 2011 272 pages
3.94
500+ ratings
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Key Takeaways

1. Online tools are transforming scientific collaboration and discovery

I believe that the process of science—how discoveries are made—will change more in the next twenty years than it has in the past 300 years.

Networked science. The internet and digital tools are enabling new forms of large-scale scientific collaboration. Projects like the Polymath Project in mathematics and Galaxy Zoo in astronomy demonstrate how online platforms can coordinate the efforts of many researchers and citizen scientists to tackle complex problems. These tools allow expertise to be shared more fluidly across traditional boundaries.

Faster progress. By restructuring how scientists communicate and work together, online tools are accelerating the pace of discovery. Ideas can be shared and built upon more rapidly, data can be analyzed collaboratively at massive scales, and specialized knowledge can be applied where it's most needed. This is leading to breakthroughs that would have been difficult or impossible under traditional models of scientific work.

2. Collective intelligence can be amplified through digital platforms

Online tools create a shared space where this can happen, a short-term collective working memory where ideas can be rapidly improved by many minds.

Harnessing diverse expertise. Online platforms allow large groups to combine their knowledge and skills in powerful ways. Projects like the MathWorks programming competition demonstrate how collective problem-solving can outperform even top individual experts. Key to this amplification of intelligence is:

  • Enabling microcontributions from many participants
  • Providing rapid feedback loops
  • Allowing dynamic allocation of effort
  • Creating shared information spaces

Designed serendipity. Well-designed collaborative systems increase the chances of making unexpected connections and insights. By exposing ideas to a cognitively diverse group, breakthroughs can emerge that no individual would likely have reached alone.

3. Open data and shared knowledge accelerate scientific progress

Information not on the network can't do any good.

Building a data web. Projects like the Sloan Digital Sky Survey in astronomy and GenBank in genetics are creating vast, open repositories of scientific data. This enables:

  • Reuse and reanalysis of data by many researchers
  • Discovery of patterns across large datasets
  • Rapid dissemination of results

New forms of publication. Open access journals and preprint servers like arXiv are changing how scientific knowledge is shared. This allows faster circulation of ideas and broader access to cutting-edge research. The focus is shifting from protecting intellectual property to maximizing the impact and reuse of scientific work.

4. Citizen science is democratizing research and expanding participation

We are reinventing discovery, and the result will be a new era of networked science that speeds up discovery, not in one small corner of science, but across all of science.

Engaging the public. Projects like Galaxy Zoo and Foldit show how non-professionals can make meaningful contributions to scientific research. This expands the pool of human intelligence applied to problems and helps bridge the gap between science and society.

New roles and identities. Citizen science is blurring the lines between professional and amateur researchers. It allows people to engage with science in more active ways, potentially sparking broader interest and science literacy. However, it also raises questions about how to properly credit and integrate diverse contributions.

5. New digital tools are changing how scientific knowledge is created and shared

We are, piece by piece, assembling all the world's knowledge into a single giant edifice.

Data-driven discovery. Massive datasets and new analytical tools are enabling forms of scientific insight that go beyond traditional hypothesis-driven approaches. Examples include:

  • Using Google search data to track disease outbreaks
  • Mining astronomy data to discover new celestial objects
  • Analyzing genomic data to uncover links between genes and diseases

Machine-aided science. Artificial intelligence and machine learning are increasingly being applied to scientific problems, augmenting human capabilities. This ranges from automating routine tasks to uncovering patterns in complex datasets that humans struggle to perceive.

6. Open science faces cultural and institutional barriers

To take full advantage of modern tools for the production of knowledge, we need to create an open scientific culture where as much information as possible is moved out of people's heads and laboratories, and onto the network.

Misaligned incentives. The current academic system primarily rewards publishing papers in prestigious journals. This discourages sharing of data, code, and ideas before formal publication. Scientists often hoard knowledge to maintain competitive advantage.

Resistance to change. Many scientists are hesitant to adopt new, more open ways of working. Concerns include:

  • Fear of being scooped by competitors
  • Lack of recognition for non-traditional contributions
  • Comfort with established practices
  • Time required to learn new tools and workflows

7. Incentives and policies can drive a shift toward more open science

Let's look at some practical steps that everyone, from working scientists to members of the general public, can take toward this end.

Funding mandates. Grant agencies are increasingly requiring open access publication and data sharing. This leverages their influence to change scientific norms and practices.

New metrics. Developing ways to measure and credit diverse scientific contributions beyond formal papers can incentivize more open behaviors. This might include metrics for:

  • Dataset downloads and reuse
  • Code contributions
  • Blog posts and other informal communications
  • Citizen science participation

Cultural change. Ultimately, widespread adoption of open science practices requires shifting the values and norms of the scientific community. This involves education, leading by example, and creating supportive environments for open collaboration.

8. Data-driven intelligence is enabling new forms of scientific insight

We are, in fact, at a unique moment in history: for the first time we have an open-ended ability to build powerful new tools for thought.

Finding hidden patterns. Advanced data analysis and machine learning techniques can uncover relationships in scientific data that humans struggle to perceive. This is leading to unexpected discoveries across fields.

Augmenting human intelligence. Rather than replacing scientists, data-driven approaches are best viewed as tools to enhance human capabilities. They can:

  • Automate routine tasks
  • Suggest hypotheses for testing
  • Identify promising areas for further investigation
  • Combine diverse datasets in novel ways

New explanation paradigms. As scientific models become more complex and data-driven, traditional notions of scientific explanation may need to evolve. There's a tension between human-interpretable theories and highly accurate but opaque computational models.

9. Science's relationship with society is being redefined by digital tools

We have an opportunity to change the way knowledge is constructed.

Broader access. Open access publishing and online scientific resources are making cutting-edge research available to a much wider audience. This has the potential to:

  • Increase public understanding of science
  • Enable more informed decision-making
  • Inspire more people to engage with scientific topics

Two-way communication. Science blogs, social media, and other platforms are creating new channels for dialogue between scientists and the public. This allows for:

  • Faster dissemination of scientific findings
  • More direct engagement with societal concerns
  • Greater transparency in the scientific process

Policy implications. As scientific information becomes more widely accessible, it may change how science informs public policy. There are both opportunities for more evidence-based decision-making and challenges in ensuring proper interpretation of complex scientific findings.

Last updated:

FAQ

What's Reinventing Discovery: The New Era of Networked Science about?

  • Networked Science Focus: The book explores how online tools and platforms are revolutionizing scientific research, moving away from traditional methods to more collaborative and open approaches.
  • Collective Intelligence: It emphasizes the power of collective intelligence, where both professionals and amateurs contribute to scientific discoveries through online collaboration.
  • Cultural Shift: Michael Nielsen argues for a cultural change in the scientific community towards openness and sharing, which is essential for leveraging the full potential of networked science.

Why should I read Reinventing Discovery by Michael Nielsen?

  • Modern Science Insights: The book provides a comprehensive overview of how technology is reshaping scientific inquiry, making it essential for anyone interested in the future of science.
  • Real-World Examples: Nielsen uses compelling case studies, such as the Polymath Project and Galaxy Zoo, to illustrate the practical applications of networked science.
  • Visionary Perspective: It offers a forward-looking perspective on how open science and data sharing can accelerate discoveries, relevant for scientists, policymakers, and the general public.

What are the key takeaways of Reinventing Discovery?

  • Discovery Transformation: The book argues that scientific discovery will change more in the next twenty years than it has in the past 300 years.
  • Open Science Importance: Nielsen emphasizes the need for a more open approach to science, advocating for data sharing and collaboration across disciplines.
  • Collective Intelligence Power: The author highlights how online tools can harness collective intelligence, allowing diverse groups to tackle complex scientific problems more effectively.

What are the best quotes from Reinventing Discovery and what do they mean?

  • Internet's Impact: "The internet is clearly the revolutionary technology of this generation of astronomer," highlighting the transformative impact of the internet on scientific research.
  • Reinventing Discovery: "We are reinventing discovery, and the result will be a new era of networked science," encapsulating the book's central theme of collaborative efforts leveraging technology.
  • Potential of Open Data: "If we could do that, cutting out the slow and expensive X-ray diffraction step, we’d go from knowing the shape of 60,000 proteins to knowing the shape of millions," illustrating the potential of open data and collaborative tools.

How does Reinventing Discovery define collective intelligence?

  • Enhanced Problem-Solving: Collective intelligence is described as the enhanced problem-solving ability that emerges when groups collaborate using online tools.
  • Cognitive Amplifiers: These tools act as cognitive amplifiers, enabling individuals to contribute their unique insights and expertise to a shared goal.
  • Success Examples: Nielsen provides examples, such as the Polymath Project, to illustrate how collective intelligence can lead to significant advancements in knowledge.

What role does online collaboration play in scientific discovery according to Reinventing Discovery?

  • Increased Efficiency: Online collaboration allows scientists to work together across geographical boundaries, speeding up the discovery process and enhancing productivity.
  • Diverse Expertise: It enables the pooling of diverse knowledge and skills, leading to innovative solutions that might not be possible through individual efforts.
  • Real-Time Feedback: Online platforms facilitate immediate feedback and discussion, fostering an environment where ideas can be rapidly tested and refined.

What is citizen science as described in Reinventing Discovery?

  • Public Participation: Citizen science involves engaging non-professionals in scientific research, allowing them to contribute to data collection and analysis.
  • Empowerment of Amateurs: The book highlights how citizen science empowers individuals to participate in scientific inquiry, breaking down traditional barriers.
  • Successful Projects: Examples like Galaxy Zoo and Foldit demonstrate the potential for collective intelligence to yield valuable scientific insights.

How does Reinventing Discovery address the challenges of data sharing in science?

  • Cultural Resistance: The book discusses the reluctance of scientists to share data due to concerns about competition and potential loss of intellectual property.
  • Need for Open Data: Nielsen advocates for a cultural shift towards open data, emphasizing that sharing data can lead to greater scientific advancements.
  • Successful Models: Projects like the SDSS and the Human Genome Project are cited as examples of how open data can benefit the scientific community.

What is the significance of the term "data-driven intelligence" in Reinventing Discovery?

  • Extracting Data Meaning: Data-driven intelligence refers to the ability of computers to analyze vast amounts of data to find patterns and insights that humans might miss.
  • Complementary to Humans: The book argues that data-driven intelligence can work alongside human intelligence, enhancing our ability to solve complex problems.
  • Scientific Examples: Nielsen cites examples like Google Flu Trends, demonstrating how data-driven intelligence can lead to significant scientific discoveries.

How does Reinventing Discovery suggest we incentivize open science?

  • Reputation Economy: The author proposes expanding the scientific reputation economy to include contributions beyond traditional papers, such as data sharing and code development.
  • Grant Agency Policies: Advocates for grant agencies to implement policies requiring open data sharing and public engagement to compel scientists to adopt open practices.
  • Community Engagement: Encouraging scientists to participate in open science initiatives can help shift cultural norms towards collaboration and knowledge sharing.

What is the Polymath Project mentioned in Reinventing Discovery?

  • Collaborative Problem Solving: The Polymath Project is an online initiative where mathematicians collaborate to solve complex problems collectively.
  • Open Invitation: Initiated by mathematician Tim Gowers, it invited anyone to contribute ideas and solutions through a blog.
  • Success Story: Within 37 days, the project solved the original problem and tackled a more complex issue, illustrating the potential of collective intelligence.

How does Reinventing Discovery address the future of scientific research?

  • Open Science Movement: The book envisions a future where scientific research is more open and collaborative, with data shared freely among researchers.
  • Technological Integration: Nielsen predicts that advancements in technology will continue to enhance our ability to analyze and interpret vast amounts of data.
  • Collective Problem Solving: The future of science will increasingly rely on collective intelligence, enabling diverse groups to tackle complex challenges more effectively.

Review Summary

3.94 out of 5
Average of 500+ ratings from Goodreads and Amazon.

Reinventing Discovery receives generally positive reviews, praised for its exploration of open science and collaborative research. Readers appreciate Nielsen's insights on leveraging technology for scientific advancement and his vision for a more open, networked approach to discovery. Some find the book repetitive or lacking in certain areas, but many consider it a thought-provoking read on the future of scientific collaboration. Criticisms include occasional overreliance on specific examples and a need for more diverse perspectives from different scientific fields.

Your rating:

About the Author

Michael Nielsen is a physicist and quantum computation expert who shifted his focus to promoting a revolution in scientific practices. He advocates for open science, data sharing, and collaborative research through online platforms. Nielsen's writing style is described as clear and engaging, combining scientific rigor with accessible explanations. His work extends beyond this book, including essays on metascience and a popular machine learning text. Nielsen actively encourages scientists to embrace new technologies and collaborative approaches, viewing them as crucial for accelerating scientific progress in the digital age.

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