PerspectiveComputer Science

Science 2.0

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Science  07 Mar 2008:
Vol. 319, Issue 5868, pp. 1349-1350
DOI: 10.1126/science.1153539

The growth of the World Wide Web and the spread of cell phones and WiFi continues to reorder whole disciplines and industries. Entrepreneurs, policy-makers, and researchers have recognized that increased collaboration through these socio-technical systems offers compelling opportunities for business, education, national security, and beyond (1). It is time for researchers in science to take network collaboration to the next phase and reap the potential intellectual and societal payoffs (24).

Successful scientific collaboratories among genomic researchers, engineering innovations through open-source software, and community-based participation in cultural heritage projects are all early indicators of the transformative nature of collaboration (5). eBay, Amazon, and Netflix have already reshaped consumer markets, while political participation and citizen journalism are beginning to change civil society. Patient-centered medical information and secure electronic health records are improving health care while creating opportunities for clinical research. MySpace and Facebook encourage casual social networks, but they may soon play more serious roles in facilitating emergency/disaster response (6). Social media platforms such as Wikipedia, flickr, and YouTube are also stunning success stories of Web-based contributions.

Understanding these collaboration-centered socio-technical systems could accelerate their adoption and raise their benefits. However, researchers will need to develop new ways of studying these complex interactions. Science 1.0 will continue to be important, but new kinds of science, which I call Science 2.0, are needed to study the integrated interdisciplinary problems at the heart of socio-technical systems. Science 2.0 will be especially important to meet the design challenges in secure voting, global environmental protection, energy sustainability, and international development among many others.

The guiding strategies of Science 1.0 are still needed for Science 2.0: hypothesis testing, predictive models, and the need for validity, replicability, and generalizability. However, the Science 2.0 challenges cannot be studied adequately in laboratory conditions because controlled experiments do not capture the rich context of Web 2.0 collaboration, where the interaction among variables undermines the validity of reductionist methods (7). Moreover, in Science 2.0 the mix of people and technology means that data must be collected in real settings (see the figure). Amazon and Netflix became commercial successes in part because of their frequent evaluations of incremental changes to their Web site design as they monitored user activity and purchases.

Political networking.

Collaboration between pairs of U.S. senators is shown by connecting links. The Democratic senators (blue) are at the left and Republican senators (red) at the right; Sanders and Lieberman (magenta) are independents. Brownback and McCain were campaigning for the presidency and did not vote often enough to be linked. Science 2.0 must develop tools like this to analyze human relationships and collaborations (16).

CREDIT: SOCIALACTION PROJECT, HUMAN-COMPUTER INTERFACE LABORATORY/UNIVERSITY OF MARYLAND

Researchers who wish to foster online health care information groups or citizen journalism, for example, need fresh research methods and theories (8, 9). Individual outcomes are difficult enough to study, but understanding why the Google, YouTube, or Facebook communities succeeded in the face of lively competition is still more challenging. These socio-technical systems are best studied at scale, in the real world, by rigorous observations (studying successes and failures), carefully chosen interventions (changing interfaces or privacy rules), and ambitious data collection (analyzing all public user activity). When adequately replicated, these quantitative and qualitative empirical studies can lead to predictive models and effective simulations that guide future designers and researchers.

Science 1.0 heroes such as Galileo, Newton, and Einstein produced key equations that describe the relationships among gravity, electricity, magnetism, and light. By contrast, Science 2.0 leaders are studying trust, empathy, responsibility, and privacy. The great adventure for the next 400 years will be to define, measure, and predict the interaction among these variables so as to accelerate scientific discovery, engineering innovation, e-commerce, and education (10). The fivefold growth of research on privacy and trust is apparent in the past 5 years, whereas empathy and responsibility are just beginning to capture attention (11).

Science 2.0 researchers are adopting observational and case study methods as they collect quantitative and qualitative data to gain support for their hypotheses about whether trust increases empathy and whether privacy promotes responsibility (12, 13). Their work methods are in harmony with research initiatives on Web science (14), creativity support tools, online education (15), and socially networked communities, among others.

Advancing Science 2.0 will require a shift in priorities to promote integrative thinking that combines computer science know-how with social science sensitivity. Science 2.0 researchers who develop innovative theories, hypothesis testing based on case study research methods, and new predictive models are likely to lead the way. The quest for empirical validity will drive research beyond what laboratory-based controlled studies can provide, while replicability and generalizability will be achieved with greater effort through multiple case studies. Just as technology-centered researchers measured progress in petabytes of storage or petaflops of processing power, collaboration-centered researchers will measure the growth of peta-collabs of cooperation and peta-contribs of assistance.

Science 1.0 remains vital, but this ambitious vision of Science 2.0 will affect research funding, educational practices, and evaluation of research outcomes. Science funding agencies will face resistance as they promote a transformation that seeks to make a safe space for Science 2.0. Scientific journal editorial boards and conference program committees are already shifting their attention to new topics and opening their doors to new scientific research methods. Pioneering educators have begun changing their curricula, focusing on collaboration strategies and teaching new research methods. The innovators are courageously taking on new challenges, but they should be ready for the resistance to novel ideas that has always been part of science. In that way, Science 2.0 is part of a great tradition.

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