In order to operate as effective Open Knowledge Institutions, universities need to implement the principle of subsidiarity: that responsibility for decisions and actions resides as close as possible to the makers of knowledge.
Open Knowledge Institutions model open behaviours in their mechanisms of knowledge coordination. In order to operate as effective Open Knowledge Institutions, universities need to implement the principle of subsidiarity: that responsibility for decisions and actions resides as close as possible to the makers of knowledge.
Open knowledge systems are harder to establish, monitor and control than closed systems but generally bring the reward of greater efficiency and productivity. Through their commitment to forms of collegiality and diffuse accountabilities, universities are the ideal institutional base for purveying open knowledge in broader society; and also to act as hubs for extended community networks.
Coordination, however, also involves mechanisms of control and accountability, as required by the rules of the institution itself, by the laws of the land, or by the mandates of external regulators. Coordination of an Open Knowledge Institution requires a full range of nurturing, advisory, prioritised, mandatory and prohibitory mechanisms. Delineation of each form of coordination requires a general principle of administrative positioning, in keeping with the nature and purpose of universities in the twenty-first century. Universities have traditionally been the source of expert, mandated knowledge communicated through policed pathways such as peer review. They now find themselves increasingly challenged by other forms of less authorised but no less powerful knowledge.
A principle that has often fostered the development of expert knowledge is subsidiarity. It is also particularly suitable for the development of Open Knowledge Institutions. The University of Oxford, for instance, has included subsidiarity as a key priority in its strategic plan, believing that it should apply at all levels of the university’s operations and as both an academic and an administrative principle.
Subsidiarity requires that responsibility for decisions and actions resides as close as possible to the makers of knowledge, that is, at the lowest possible point in an administrative hierarchy. An Open Knowledge Institution will have a high and comprehensive internal delegation of its power. If accountability could be located at the level of Faculty or Department or Centre, for instance, subsidiarity suggests that the Centre level is most appropriate. The principle of subsidiarity thereby affords maximal empowerment to the actual producers of knowledge, but also stresses their accountability for that production and dissemination of that knowledge, within the prevailing rules or regulations. This is in contrast to top-down control mechanisms, which, while easier to administer, strip authority from the actual producers of knowledge, thereby diminishing the rewards from but also responsibility for their knowledge-making activities.
Because an Open Knowledge Institution involves extensive porosity with external communities and individuals and, hence, a partial responsibility for such activity, it has to have flexibility in all its negotiations with these external bodies, each of which will have their own forms of facilitation and control. These external parties include private companies, other institutions (not necessarily education or research focused or dedicated to open knowledge), professional bodies, funding authorities, bureaucracies and regulators. Issues of different disciplinary traditions, conflicting ethics, policy formulations or change mechanisms, as well as naked self-interest, need to be encompassed in such negotiations (and subsequent documentation) of universities in developing and maintaining their open knowledge roles.
The danger in fostering open knowledge is that major breaches of agreements or regulations do occur. The 2018 Facebook-Cambridge Analytica debacle, also involving the University of Cambridge and its staff, highlights the need for careful monitoring and control, not just of knowledge and data flows but also of personnel with multiple allegiances. Institutional ethics committees must also establish new regulations around individual-level data; to ensure that open data does not threaten the privacy of research subjects or put them at undue risk.
The solution to such problems is not, however, for universities to default to closed knowledge systems.
5.2 Knowledge Functions
Coordination in Open Knowledge Institutions involves both internal and external participants in creating, mediating and governing knowledge. This requires navigating a complex interplay of various actors, with differing levels of participation and control in the system and where the boundary between external and internal is increasingly and productively blurred. Functions of the knowledge production process in the university setting include:
Knowledge Regulation: This function is distributed throughout the organisation using the principle of subsidiarity. In the Open Knowledge Institution, protocols coordinate at the level of responsibility. Creative Commons is one example of scalable knowledge regulation.
Data Sources: Human subjects are the source of data from which knowledge is produced in the medical and social sciences. However, the recent use of data from social media and sensor technology has vastly increased the level of personal data that is constantly recorded and used for research purposes. Research participants are increasingly unaware of their participation in research (e.g. as demonstrated by Kramer et al., 2014 in the Facebook emotional contagion experiment ). Therefore, we consider those individuals who are generating data for research, with or without consent, to be participants in an open knowledge environment, requiring respect for these individuals and consideration for their privacy and risk.
Spatial Coordination: The open knowledge institution has a physical as well as intellectual location. Campuses need coordination as well as courses. University visitors organise their interaction with the institution (cars, coffee, infrastructure, buildings) around campus spaces. Users of the Open Knowledge Institution also find places in which to coordinate their own activities; an 'open campus' will often present as a public park or cityscape rather than as an institution.
Coordination of Openness: Openness does not just happen. The Open Knowledge Institution values standardised protocols, interoperability, ensures the findability of open data and archives and keeps its web interface legible to those within and outside of the institution. The Open Institution coordinates its navigability.
Knowledge Production: An Open Knowledge Institution takes a social approach to the production of knowledge. This includes the contribution of identifiable social groups such as Indigenous populations, citizen scientists, etc., but also the combined efforts of many people in the research process.
Knowledge Mediation: This function provides links amongst knowledge makers and knowledge users. As a hub for networked science and knowledge production, Open Knowledge Institutions play a crucial role in mediating and facilitating knowledge creation and communication.
Knowledge Curation: In the open environment, the discoverability, accessibility, and interoperability of knowledge resources are as important as their creation. Open Knowledge Institutions need to coordinate production, curation, exhibition and archiving.
Knowledge Use: The Open Knowledge Institution does not constrain knowledge use – it coordinates feedback and develops protocols for the legal, ethical, and commercial use of knowledge products.
Social Benefit: It is always challenging to measure the benefits of knowledge for society at large. Some academic evaluation systems discourage researchers from engaging with external parties who do not directly interact with the institution or the knowledge creation process, for example: patients who may benefit from the outputs of medical research; lifelong learners who use open educational resources developed from research outputs; ethnic and minority groups who have been the subject of research, among others. Such groups are a crucial part of the impact profile of institutional research. An Open Knowledge Institution uses a participatory approach to identify problems and set research agendas in dialogue with external parties. An example would be the efforts of the Dutch government (via The Netherlands Organisation for Scientific Research) in inviting citizens to participate in the development of the national research agenda; making visible the social benefits of publicly-funded research.
Open Knowledge Institutions facilitate participation rather than taking a top-down, controlling and exclusive approach. Coordination procedures seek to enable productive and collaborative linkages with various actors, stakeholders, grassroots, and regulators.
Inclusive coordination not only provides platforms for dialogue among participants but also imagines permeability among types of knowledge participant. That is, an Open Knowledge Institution imagines the possibility that a knowledge 'consumer' can become a user; that a 'beneficiary' can become a maker. All roles add value and the possibilities for simultaneous and sequential embodiment in various roles must be maintained. Furthermore, it must be recognised that knowledge production involves many different value systems. An institution may be subject to certain regulatory frameworks that a knowledge-maker may not. In turn, the knowledge-maker may be responding to disciplinary pressures that are external to the institution. Coordination requires awareness of and attention to these competing priority and value systems.
Sensitive coordination will always maintain a precarious balance between openness and control. Actors within the knowledge system are subject to different pressures and regulation. To attend to these pressures, coordination must ensure maximum flexibility while meeting the needs of accountability bodies and regulatory agencies. Given that systems are apt to evolve to a naturally closed state, mechanisms must be in place to incentivise and reward openness.
5.3 Coordination and Indicators
In 1991, Paul Ginsparg launched arXiv, the first Internet-based preprint server. It became one of the first internationally used scholarly web resources. The intention was to provide an online mechanism to facilitate the established system of pre-print exchange within the field of high-energy physics. The server became well-established, not only in physics but also in mathematics and computer systems and is now the largest operating e-print system in the world. This system has replicated many traditional journal functions, the certification of priority claims and dissemination being chief among these. The ubiquity of this platform has led to a scenario in which there is a high risk to maintaining closed dissemination (i.e., publishing exclusively in a non-open access journal). Those who choose, for example, to publish in a non-open access journal may be undercut by those who make their work available on arXiv. High prestige journals have acknowledged and validated this approach, noting the benefits that accrue to scholars through openness (Nature, 4 April 2018).
Despite these successes, many disciplines still encourage closed systems. Chemistry, for example, is a notable domain with low rates of openness in scholarly communication. This disparity demonstrates the need for coordination: it is not strategically beneficial to be one open institution among several closed systems. An entire system must adapt in order for the system to regulate openness effectively and comprehensively.
If universities were to shift on a large scale to act as Open Knowledge Institutions, this would tend to shift the equilibrium position within the overall system towards open as a default position. To depart from this norm, therefore, would come at a cost to the closed institution.
Indicators are tools commonly used to incentivise behaviour in academic institutions. In a well-coordinated environment, indicators can be useful tools for developing and operationalising norms. By developing a set of indicators of openness, therefore, it would be possible both to examine the growth of this openness and to equate prestige and reputation markers with the ideals of openness.
There are, of course, certain advantages and disadvantages to being a first-mover in the establishment of a new system. High prestige institutions have the greatest potential risk, with little initial benefit. These institutions are prestigious on the basis of established systems of indicators, therefore have little incentive for change. However, they also have the greatest potential to affect the system. For example, in the establishment of open access mandates, the adoption of a policy at Harvard University (2008) and, at around the same time, at the US National Institutes of Health (NIH), were fundamental to establishing the open access movement as both legitimate and aspirational.
Notably, these examples involved prestige, but also exposed negative effects of being closed. In the case of the National Institutes of Health mandate, researchers who did not comply with the requirement to deposit publications in an open access repository would not receive funding. In this way, there is a coercive aspect to systemic coordination: one must empower individuals within the system, but there also must be types of control to encourage the shift to participation in open practices.
One of the difficulties in coordinating open knowledge practices at the institutional level is that institutions are often subordinate to disciplines in terms of authority. Institutions must be responsive to regulators, yet individuals often garner recognition and prestige not from their institutions but through their disciplines. There are, of course, examples of disciplines that have been heavily supported and thereby regulated through governmental and other institutional initiatives (such as nanoscience, neuroscience, and genetics). However, by and large, academics are responsive to disciplinary traditions. Therefore, coordination must involve engagement with these disciplinary communities. Decision-makers within disciplinary communities must be engaged with and promote cultures of openness; for example, editors and governing boards of professional societies. Without buy-in from these highly influential communities, the shift to open institutions at system scale is likely to fail.
A coordination scheme should be consistent with overall institutional tone. That is, coordination of an open knowledge institution requires that openness be embedded in the strategic plan of the institution and be pervasive across all practices at the institution. An ideology of openness cannot be mere rhetoric. Rather, an institution must be open across the range of education, research, negotiations with staff and alumni, development and philanthropic engagements. There must be purposeful coherence in an Open Knowledge Institution: one cannot have a closed education system in an open knowledge university. An open knowledge system requires coordination and coherence across all activities of the system.
5.4 Key Issues of Coordination
Coordination requires both a change in cultural values and also requisite infrastructure. Returning to the example of the United States National Institutes of Health, one can see the necessity of supporting platforms for open knowledge practices. The implementation of the National Institutes of Health Public Access Plan involved coordination not only with federally-funded investigators but also with the publishers to which these investigators submitted their research, and with the US National Library of Medicine who maintained a repository of Open Access articles. The strong coordination among these different actors, plus the financial support of infrastructure, made the NIH Public Access plan a success. At present, there is nearly 100% compliance among NIH-funded researchers. This is in stark contrast to the US National Science Foundation mandate, effective as of August 2013, which did not involve coordination among stakeholders nor any additional funding for infrastructures for openness. In turn, the rates at which NSF-funded researchers are making their research openly available is only slightly above the rates of the non-funded researchers in the US (and compliance is at less than 50%) (Larivière & Sugimoto, 2018). Coordination must, therefore, involve communication among many regulators and service providers, as well as a commitment to infrastructure.
An Open Knowledge Institution cannot exist in isolation. The infrastructure for Open Knowledge Institutions involves coordination not only within institutions but also across them. Technical solutions for an open knowledge institution must be coherent with the principles and values of open knowledge, that is, they must facilitate maximal involvement and be inherently transparent. Blockchain technology, which is the emerging consensus protocol behind cryptocurrencies such as Bitcoin, provides an example of a technology that embodies the ideology of openness. Blockchain technology is, in essence, an open source software protocol for creating and transacting value in systems without relying on centralised institutions to validate or authenticate changes to the underlying facts or entries into the ledger. Blockchain technology can be used to record and authenticate, through timestamping and hash signatures, the exact moments of creation and to verify the originality of documents and content. This becomes a basic technology for the creation of the digital infrastructure of open systems through decentralised record keeping, auditing, verification and through cryptocurrency tokenisation, to create high-powered incentives for contribution to common pool knowledge and content resources.
While the primary focus of this book is on open knowledge and the university, the question of coordination goes far beyond the university campus. Given the important (although diminishing) role of government-originated funding to a university’s accomplishment of its purposes in so many countries, the effective coordination of open knowledge at a systemic (macro) level hangs upon effective public policy that informs funding distribution. The strengthening requirement over the last decade that recipients of public funding must provide public access to the research or educational findings resulting from such investment has been a major factor in fuelling the open knowledge movement. This affects not just the various open access initiatives in publication but also denser networking across institutional and disciplinary boundaries in educational and research developments. This requirement, however, raises important questions regarding coordination of multiple actors and roles in such areas as intellectual property (IP) and patents.
The growth of industry linkages and public-private partnerships has raised tricky questions about the limits of exclusive rights to research, educational findings and to related materials. What is commercial-in-confidence, and for how long it might remain so, are important questions that do not find uniform answers across institutions, especially when private corporations are substantial funders of the research. While the conditions of receiving public funding now increasingly involve public access requirements, the situation becomes murkier when commercial partners, particularly commercialising partners, are also involved. The mixed model of journal publication that currently prevails leaves important questions of IP ownership unresolved and highlights the continuing danger of capitalistic entrapment of institutions, scholars, or entire systems, and their (sometimes enforced) 'alienation from the products of their intellectual labours'.
As tech giants such as Google and Facebook have transformed into the providers of digital knowledge infrastructure, operating under a model of platform capitalism, Open Knowledge Institutions also need to develop strategies and protocols regarding content copyright and data uses while utilising these private platforms. If Open Knowledge Institutions are to grow and thrive, strong institutional leadership and cross-institutional coordination are needed, in defence of the default position of open knowledge management. An Open Knowledge Institution will by necessity evolve in its funding sources and financial planning, both because of its greater integration into a network of associated communities and because of a change away from atomised, internal cost-recovery silos to a more institutional view of the costs and benefits of open knowledge initiatives. Along with these initiatives will come new emphases in infrastructure development and infrastructure partnering. A global open knowledge infrastructure is needed and is being developed collaboratively by numerous like-minded open initiatives and communities.
Unlike corporate infrastructures such as Facebook, open infrastructures are built upon platform cooperativism, open source models, and knowledge commons, and technologically enable and facilitate the exchange of knowledge resources in digital forms and in interoperable ways between different formats, mediators and platforms. Open Knowledge Institutions need to harness open infrastructure and also to take an active part in its collaborative development. The coordination of these initiatives will require academic and administrative leaders who are more negotiational in style and more multi-layered in managerial focus. As the articulators of institutional tone (influencing the ratio of consonance and dissonance among partners), these leaders will require specific training. Those to whom they are accountable will need re-education in the priorities of the less autonomous, more connected open knowledge institution.
We have largely focused on the benefits of Open Knowledge Institutions, but we also plainly recognise that there are costs. Costs are usefully separated into fixed costs of transition to an open state, which are the upfront costs of rebuilding and retooling universities, and the ongoing variable costs of maintaining open knowledge institutions. Fixed costs could be considerable, not necessarily as direct financial costs of new capital and kit, but costs of disruption of standard operating procedures, protocols and expectations. These are upfront costs of leadership and managerial effort and attention, as much as of line items in budgets. There is, therefore, a role for top-down coordination from federal and state ministries of education, science and industry to coordinate these endeavours in order to spread these costs across institutions and to publicly fund the transition.
Although substantially different, this principle has many similarities with a phenomenon I have been studying in the past 5 years within the scope of my PhD on Design [learning]. It’s called Stigmergy, “a mechanism of indirect coordination, through the environment, between agents or actions. The principle is that the trace left in the environment by an action stimulates the performance of a next action, by the same or a different agent. In that way, subsequent actions tend to reinforce and build on each other, leading to the spontaneous emergence of coherent, apparently systematic activity.” (wikipedia) (Wikipedia being an obvious evidence of stigmergy). Mark Elliot is an australian researcher on this topic and the way it can be connected with cognition and “education”.