In 1613, a scholar named Barnaby Rich wrote: âOne of the diseases of this age is the multiplicity of books! They doth so overcharge the world that it is not able to digest the abundance of idle matter that is every day hatched and brought forth into the world.â This cry could easily be uttered now, in the current age, when we feel overwhelmed by the production of information. But the sentiment of being overwhelmed by the volume of published knowledge is not new. Even the Bible warns against becoming distracted by reading too many books: âOf making many books there is no end, and much study wearies the body.â1 Yet, today, in addition to the volume of books, we have a proliferation of sources of knowledgeâblogs, e-zines, proceedings, websites, audio and video presentations (some might say this is all âinformationâ rather than knowledge, but we will discuss that)âcausing us to sense that a transformation of deeper patterns is under way. The flood of information is pressing upon us in a way that is shifting how we organize ourselves as knowledge users and how we task, fund, and support the institutions designed to create and use it. Perhaps we are getting closer to the vision that Lewis Thomas (1974) had, one of interliving shoals of thought: âLater, when the time is right, there may be fusion and symbiosis among the bitsâŠ.â
This book addresses a specific part of the knowledge-creating processâthe activities we call âscience,â the understanding of the natural worldâand, specifically, the abundance of and access to this information. Scientific knowledge is contained in books and articles, of course, but science is also a practice conducted through research and experimentation that has spread around the world over the three centuries that constitute the years since a rational, experimental approach was designed in Western Europe by the âInvisible Collegeâ (Crane 1972). The most basic of these activitiesâteaching and researchâare almost entirely funded by public money. Thus, it needs to be governed and accounted for to properly steward public funds. And it needs to show public benefit. This is a specific challenge of public science that creates conditions that challenge governance, as we will discuss.
Science is often referred to as a pure public good: one that is available to everyone because it is nearly impossible to exclude others and because it can be reused endlessly without depleting it. Businesses steer away from creating public goods because they cannot make a profit from something to which they cannot claim ownership. Governments generally provide for public goods and attempt to ensure the diffusion of these goods. This is truer in science than in other goods, where a large percentage of funding of basic research is the purview of governments.
Scientific knowledge is also characterized by what is sometimes called a ânetwork effectâ in that it gains value by being shared. As people grow to hold a common understanding of a natural phenomenon, such as Einsteinâs relativity, they can put that knowledge into use to create practices, technologies, or other new knowledge and commercial products, such as satellites. Similarly, think about the usefulness of knowing the properties of disease-causing bacteria first suggested by Lister and Koch, and tested by Pasteur. No doubt, your cupboard is filled with anti-bacterial products designed to combat the negative effects of these unseen critters. Similarly, knowledge about the need to replace electrolytes in children with diarrhea has instituted the simple, low-cost, and highly effective practice of rehydration therapy around the world, saving millions of lives. Scientific knowledge put into practice becomes common knowledge.
The sense of being overwhelmed by the flood of information is a fundamental human experience not necessarily limited to our time but tied to the limitations of our senses and life span. Who can really know all there is to understand about the universe, even as we revel in spectacular findings such as the existence of exoplanets? Scholars in nearly every age have complained that knowledge is coming at them too fast to digest. Philosopher Friedrich Hayek suggested that the âevolution of ideas has its own laws and depends very largely on developments that we cannot predict.â Yet, is it completely true that the laws of the development of ideas cannot be âpredicted,â as Hayek suggested? The evolution of ideas has appeared in the past to be random, the result of âserendipityââbut we perceive many phenomena as random or at least as resulting from some hidden orderâlike the formation of beehivesâuntil we understand it. Could it be possible to better understand the unfolding of abundant knowledge, especially scientific and technical knowledge, which has proved so useful? Could an improved understanding of the production of scientific knowledge help us improve outcomes and better manage the âdata deluge,â as Christine Borgman (2010) has named it? This book asks these questions and draws some lessons from the science of networks, ecosystems, and complexity itself to better understand the workings of the enterprise we call science.
Science aims to make the world a more intelligible place through observations of the many variations and differences in the natural world. This book aims to make science more intelligible to those who govern it. Science places the phenomena of the natural world within a coherent framework that makes sense in a context that transcends culture. This book explains scientific knowledge creation as networked communications that can be understood and influenced with new understandings of networks. The idea is to view scienceânot simply from the perspective of the record of its achievementsâbut as a practice of communications that has regularities that can be anticipated and, therefore, governed effectively. This exploration sheds light on the process that has been referred to as a âblack boxâ (Rosenberg 1982) or âPandoraâs Boxâ (Gilbert et al. 1984). By unpacking recent breakthroughs from network studies and complex systems theory, we can find new ways of understanding and perhaps influencing the âblack boxâ of science to improve outcomes.
The convergence of many factors makes this possible. These include the demonstrated usefulness of open scientific communication, the need to solve global problems that depend on science, the information revolution, the economic growth occurring in many parts of the world, and greater political and social openness the world over. These features of the early twenty-first century contribute to deeper patterns of change for science that make it worthwhile to take time to consider the features that make it useful and how to reimagine it for a global era. Many parts of scientific practices continue to operate as they have done for centuriesâwhite-coated men and women still swirl chemicals in a beakerâbut other parts of its practice are changing, such as a global network of seismometers that record the occurrence of hundreds of earthquakes every day across the globe. An enhanced understanding and better stewardship of the processes can also improve the ways we create and use it. After all, we âownâ itâwe pay for it and expect science to provide knowledge that we need. In many ways, society is looking to science to address the most pressing and significant problems of climate change, energy needs, food availability and security, water usage, and universal education. It is worth taking time to consider the underlying forces of organization, use, and benefits of knowledge. This book addresses these questions.
The practice called âscienceâ has undergone many shifts and changes over time. The history of science is fascinating in itself. Even the word âscienceâ was only applied in the eighteenth century to the practice of creating reproducible knowledge about the natural world. This book focuses on the future, however, and in particular on two aspects of science operating at two frontiers: one, science at the international level where the practice of scientific collaboration has been growing rapidly; and two, at the interdisciplinary frontier, where it is possible to see a good deal of what appears to be growth in the practice of âinterdisciplinaryâ science. These areas of scientific practice have not been well studied, even though they are growing rapidly. These two areas, which also intersect and overlap, are more likely than other aspects of science to operate as networks for reasons that we will discuss in the book. For reasons that will become clear as we lay out their structure and rules, networks are what you would expect to find here because of the emergence and complexity of both international (or global) science and interdisciplinary research.
Characterizing science as a network opens up new and effective ways to describe the dynamic processes. Network science has come into its own over the past two decade. An enhanced understanding of networks can help those of us who support, use, and manage science to improve the creation and dissemination of âuseful knowledgeâ as Joel Mokyr (2002) calls it in his book, The Gifts of Athenaâknowledge that is âaccumulated when people observe natural phenomena in their environment and try to establish regularities and patterns in themâ (p. 3). Mokyrâs definition is broader than the classical definition of science as verifiable knowledge about the natural world, in that âuseful knowledgeâ can include indigenous knowledge and practices that are often considered to be outside the scope of science. Thus, in Mokyrâs sense, useful (he calls it âpropositionalâ) knowledge includes informal ways of knowing about natureâclose to what the physicist-turned-philosopher, Michael Polanyi, called âtacit knowledgeââand can inclusively extend to the knowledge and practice of the artisan or the medicine woman. Local, indigenous, or folk knowledge shares the characteristics of being verifiable and reproducible, but it is not often considered to be in the realm of reproducible science even though it is useful.
The aspects of inquiry that we call science have both common and variable aspects. The common ones surround the scientific method of experimentation, reproducible results, and the communication of findings. Variables are the object of study, how it is done, who pays for it, and how it is shared. These variables are often determined by social or political factors, and are therefore subject to change. These are the factors that motivate this particular inquiry. The research for the book was motivated by the observation that, for many of the policymakers, philanthropists, and investors seeking to include more people into the practice and understanding of science, the shifts in the social and political aspects of science lead to frustration. For example, the European Commission has invested billions of euros in research and development, yet their scientific outputs still lag behind that of the United States in many indicators of âscientific quality.â The World Bank has provided millions of dollars in grants and loans to help poor countries develop useful knowledge, but these nations remain poor. The United Nations has encouraged science and technology investments to help the world reach the Millennium Development Goals (MDGs), yet this has not resulted in propelling the poorest peoples to achieve the hoped-for outcomes. This is not to say that there has not been progress but to note that inequality remains a problem. Science does not, in itself, reduce inequality.
Science cannot solve all these problems. Yet, among those people who seek to apply scientific solutions to these problems, we need a solid understanding of how science operates, a feature that changes to some extent with the social and political structure. Modern science has transitioned from a collection of largely independent experimentalists in the seventeenth century, to laboratory-based research supported by governments and donors in the eighteenth century. As science proved its worth, it became a profession for which young people were trained in universities, and governments increased support for it during the nineteenth century. In the twentieth century, science became largely captured by nations, and its practice was highly tied to national prestige and the service of war and economic growth. The vestiges of each of these previous eras remain, but the practice of science is undergoing a fourth metamorphosis in the twentieth-first century, shifting toward global networks that operate beyond the silos and constraints of the institutions and disciplines that defined it in earlier days.
This shift from national and disciplinary identities to locally useful, globally connected knowledge networks changes the way we organize and account for science. If the âmeasureâ of science were inverted from a national competition toward one of measuring increased welfare (due to integration of useful knowledge), would the European Commission still view itself as suffering a âEuropean paradoxâ when compared to the United States? If local knowledgeâeven know-how emanating from the medicine woman and local artisansâwere to be considered as valuable as scientific publications, would the poorest countries still be considered to be outside the realm of the âknowledge societyâ? If the United Nationsâ well-meaning MDGs were met with an integrative process linking scientific knowledge to the underlying goals, would the world be closer to closing gaps in clean water, maternal health, or clean food? Right now, we can only answer, âperhaps.â But it is the competitive and exclusive face of science that has left some feeling âbehind.â A change in the way we think about science could change this for the better.
With improved insights into the knowledge-creating processâspecifically, to shift away from science as a ânational assetââto view knowledge as a networked resource operating at local, regional, and global levelsâit is possible to create new and more effective policies and governance tools to extend the benefits of science to a broader user group. The insights presented here are designed to help to improve the experimental processes and move knowledge more readily toward useful applications, increasing efficiencies, and extending science to include new participants.
The Study and Understanding of Science
The nature of science and the intricacies of its operations have been a subject of inquiry since the time of the early Greeks. Many writers have tackled the question of âwhat is scientific knowledge?â Many earlier efforts have emerged from within sociology and philosophy by scholars concerned with broad cultural implications of the impacts of scientific knowledge. Science has been seen as a blessing and a curse. It has been seen as a noble endeavor and a foolish practice. It has been held up as the pinnacle of human achievement, and it has been forced underground by political regimes threatened by it. The practice of science has shifted in scale, scope, or style along with the changes in social and information infrastructures.
Among the ideas about knowledge creation in science, perhaps the best known is The Structure of Scientific Revolutions in which Thomas Kuhn (2012) described his view of how science advances through a process of shifts between normal and revolutionary science among communities of scientists. Kuhn stated that scientists spend most (if not all) of their careers in a process of problem-solving. Their problem-solving is pursued with great tenacity because the previous experiments created accepted facts about an established âparadigm.â The paradigm tends to generate confidence that the approach being taken within that field guarantees a solution to a puzzleâthis can be called âscientific theory.â Kuhn calls this process ânormal science,â and indeed the bulk of scientific practice still looks quite similar to what Kuhn called ânormal science.â
Kuhn went on to describe how science changes in his view: as a paradigm is stretched to its limits, anomalies occurâstrange findings that fail to meet expected outcomes detailed by the existing paradigm. The accepted theory cannot fully account for or explain an observed phenomenon or data. This is the moment that Isaac Asimov calls the greater moment in science than âEureka!â but one where someone says âthatâs funny.â An example of an anomaly was made public in the summer of 2011. Scientists in Europe, testing the speed of light, could not account for an anomaly. Physicists at the Gran Sasso Laboratory, Italy, had data showing certain neutrinos moving from a site in Switzerland to the Italian site at speeds that appeared to be faster than the speed of light. Obviously this challenges accepted laws of physics. The teams considered and debated for some time, but in the end, they decided to ...