I’ve just returned from the Summer ESIP Federation meeting, where we held a powerful discussion about the need for data commons (plural). This discussion got hung up a bit by a lack of clarity on the definitions of the terminology (including the word “commons”) and also a general lack of knowledge about the current literature on the commons (the group were mostly Earth data scientists).
So here I want to offer some short and very basic definitions (my own) and bring up some ideas and questions that might be of value to these discussions in the future. [I will also come back to this textin the future and link to a bibliography that is just now being created by the Force11 team.]
Scholarly commons are…
Intentional communities (plural) formed around the shared use of open scholarly resources (a type of common-pool resource). Commoners work together as a community to optimize the use of the open resources they share. Scholarly commons are resource-near communities. They have an immediate and professional stake in the open resources they want to use. The whole community assumes a stewardship role toward these resources. These groups are self-defining and self-governing, each with their own emergent rules. Since scholarly commons are built upon open public resources, anybody on the planet can access them. When these are digital resources, they are not diminished by overuse. However, these resources cannot be sustained without the commons, or some other economy. These commons represent the social/cultural destination for any number of open-science efforts. (Note: Principles that can help all scholarly commons work together at the social level and as technical infrastructure are being considered at this moment in Force11.)
Scholarly commoners are…
Members of these intentional communities, with the freedoms and responsibilities that their communities provide and demand. Commoners work for the benefit of the whole community and for the sustainability of its open, shared scholarly resources. An individual commoner may belong to several commons. It is the role and the goal of commoners to help these open, shared resources flourish.
Scholarly commoning is…
The practice (and an attitude) that commoners bring to the scholarly commons. It begins with a logic of abundance, and depends on an active culture of sharing. Commoning is the activity to build and sustain the commons through shared practice (thanks to Cameron Neylon for this wording).Scholarly commoning is also imbued with an ethos of scholarship/science (however defined). Scholarly commoning informs how science can be accomplished through the use of open, shared resources (open ideas, open data, open software, open workflows, open-access publishing with open review, etc.) inside commons, instead of through other types of economies.
Can a single object in one open repository be claimed as a resource by more than one commons?
Scholarship needs to be fearless. One role of academic tenure was to protect this condition. In the face of the neoliberal market, tenure has failed in this role. Can the commons provide this protection?
Someone noted that many data objects are “uncommon” objects that require knowledge and knowhow to use and share. Scholarly commons also maintain knowledge and knowhow.
Someone said that the data commons might just be a thousand ESIPs, each one stewarding its own collections, optimizing their value, and creating APIs to share them. Sounds pretty good to me! What does everybody think?
I’ve just returned from the Summer meeting of the Federation of Earth Science Information Partners (ESIP). After nearly two decades of “making data matter”, ESIP continues to show real value to its sponsors. Indeed, the next few years might be a period where ESIP grows well beyond its original scope (remotely sensed Earth data) to tackle data and software issues throughout the geosciences. A good deal of the buzz at this year’s Summer meeting was a new appreciation for the “ESIP way” of getting things done.
ESIP champions open science at all levels, and this openness extends to everything ESIP does internally. ESIP is building a strong culture for the pursuit of open science in the geosciences, and remains a model for other volunteer-run virtual organizations (VRVO) across science domains. There are lessons learned here that can be applied to any arena of science.
I hope other agency sponsors will take note of ESIP when they propose to fund a “community-led, volunteer-run virtual organization.” In this letter I’m going to point out some central dynamics that can maximize the ROI for sponsors and enable these organizations to do their work of transforming science. One note: I am using the term “sponsor” here to designate agencies or foundations that fund the backbone organization, the staff of the VRVO. The work of volunteers is of course, not directly funded (apart from some logistic support).
The biggest picture
The real potential for any science VRVO to return value to its sponsors is realized as this organization develops into an active, vibrant community-led, volunteer-run virtual science/technology organization. To capture this value, the VRVO needs to focus on those activities that leverage the advantages peculiar to this type of organization, with special attention to activities that could not be realized through direct funding as, say, a funded research center. This is a crucial point. The real advantages that the VRVO offers to science and to its sponsors are based on the fact that it is not a funded project or center, and that the difference between it and funded centers (or facilities, or projects) is intentional and generative to its ROI.
The simple truth is that any volunteer-run organization will never be able to perform exactly like a funded center, just as centers cannot perform like VRVOs. Community-led organizations make, at best, mediocre research centers. Volunteers cannot be pushed to return the same type of deliverables as those expected by a center.
The biggest return that any VRVO will provide to its sponsors will come from circumstances where incentives other than funding are in play. In fact, adding money is generally a counter-incentive in these circumstances. Among these returns are the following:
A durable, expandable level of collective intelligence that can be queried and mined;
An amplified positive level of adoption to standards and shared practices;
An ability to use the network to create new teams capable of tackling important issues (=better proposals); and,
The ability to manage a diverse set of goals and strategies within the group, each of them important to a single stakeholder community, but all of them tuned to a central vision and mission.
Elsewhere I have outlined a larger number of such returns on investment. I continue to receive comments listing additional ones. I’ll do an updated list before the end of the year.
None of these returns can be funded directly by the sponsors, apart from supporting the backbone organization that in turn supports the VRVO. And none of these could effectively be funded through a center or other entity. They are predictable outcomes only of precisely the type of organization that the VRVO will, hopefully, achieve.
The real test for a science VRVO is to develop fully within the scope and logic of its organizational type. The concomitant test for the sponsors is to understand that sponsoring a new and different type of organization will require some new expectations and some period (a few years) of growth and experimentation to allow the virtual organization to find its own strength and limits.
Governance NOT Management
One important lesson learned at ESIP is this: governance must never be reduced to management. Funded projects and centers are managed. VRVOs are self-governed. Volunteer-run organizations are intrinsically unmanageable as a whole, and at their best. A VRVO can certainly house dozens or hundreds of small, self-directed teams where real work can be managed. ESIP “clusters” are good example. These teams can produce valuable and timely deliverables for science and for the sponsors.
The style of governance is also very important here. Attempts to shift governance away from the membership and into top-down executive- or oversight committees are always counterproductive. They give the membership a clear alibi to not care about the organization. Academics have enough alibis to not volunteer without adding this one. The members need to own the mission, vision, and strategies for the VO. Successful activities will emerge from initiatives that have been started independently and with some immediate urgency by small groups and which grow into major efforts with broadly valued deliverables. Bottom-up governance will outperform top-down management over the long term.
Science culture shifting
Probably the largest recognized impact that science VRVOs can make here—and perhaps only these can accomplish this—is to model a new, intentional cultural mode of producing science. This new cultural model will likely be centered on sharing (sharing is also one of the oldest cultural traits of science, only recently neglected). Sharing ideas. Sharing software, tools, techniques, data, metadata, workflows, algorithms, methodologies, null data, and then sharing results. Reuse needs to become a key metric of science knowledge (Cameron Neylon noted this at the original Beyond the PDF conference).
Transforming science means changing the culture of science. Science VRVOs must perform real culture work here. This is often a challenge for their sponsors, as these organizations are usually well situated at the center of the existing science culture. The key learning moments and opportunities, and perhaps the highest ROI for sponsoring a science VRVO is when this organization teaches its sponsor to change.
Three critical governance conditions any agency/foundation sponsor needs to heed.
There are three necessary conditions for an agency-sponsored, community-led organization to be accepted as legitimate by a science community.
The sponsoring agency needs to allow the community to build its own governance. Governance documents and practices are not subject to approval or even review by the sponsoring agency, apart from needing to follow standard fiduciary rules. The sponsoring agency can offer input the same way other individuals and groups do, but the community decides its own practices. The metrics for the governance are the growth of volunteer participation, and spread of community involvement, the perceived transparency and fairness of decisions, and the community’s value placed on the work being done.
The sponsoring agency has no right to review or in any way interfere with elections. All organization members have the right to run for office and to be elected.
The agency’s sponsorship is designed to help the organization grow into its potential as a volunteer-run, community-led scientific organization. The returns on investment for the agency are multiple, but do not include tasking the organization to perform specific duties, other than to improve over time.
Postscript: of course, the golden rule of any volunteer organization, new or old, is this: DFUTC.
Here is a talk I gave at the recent (Summer 2012) ESIP Federation meeting. Sharing Creativity:
I am hoping that this talk will lead to some conversations over the potential for virtual organizations to achieve, with more efficiency and effectiveness, a capacity for creativity and predictable innovation. This capacity—in large part due to Internet-enabled capabilities for coordination and collaboration— can, I believe, rival (at various scales) the capabilities of dedicated R&D facilities/programs such as Bell Labs and Xerox PARC on the corporate side, and the Manhattan Project and the Apollo program on the government side.
Large research and development operations such as these were built as national laboratories, with hundreds or thousands of employees and forefront facilities. They were designed to assemble a critical mass of talent and direct this toward innovation. They were also enormously expensive: the Apollo program had cost more than $25 billion by 1973 (in 1973 dollars). The successful ones are rightfully famous.
Today’s top technology companies (Apple and Google, for example) often add to their innovation potential by buying forefront start-up companies, as much for their talent as for their technology. Their goal in a highly competitive market is to own enough talent, enough intelligence, enough creativity, to stay ahead of their rivals.
The basic business-school rule for improving the odds for successful innovation is to assemble a requisite variety of knowledge: a range of knowledge at least as large as the problem being tackled. The three ways to do this are the following: Hire it (add to your team); Grow it (reeducate your team); and, Buy it (purchase a rival company/team). All of these methods assume that you need to own the requisite variety of knowledge.
Science, on the main, has only one rival: the unknown. Scientists are relatively free to seek out new collaborators from anywhere. And, through Internet-based services, they are now enabled to become collaborators everywhere. This is one reason why the NSF has been promoting virtual organizations and research networks as the future of science collaboration (instead of building new centers at institutions). A good part of the potential that virtual organizations offer government and private funding agencies comes from a new logic for innovation: assemble and share the requisite variety of knowledge. With the right sort of organizational governance and funding, a virtual organization can achieve what the older “think tank” R&D centers could: predictable, successful innovation.
There are some social aspects of the ESIP Federation that might be key to this capacity for creativity. These aspects are not secret, however, and can be fully copied and applied in other arenas. They are also not expensive (the Federation budget is remarkably small), but they are of great value, in that they have been worked upon by dozens of volunteers over the course of more than a decade.
Virtual organizations (VOs) come in many forms and sizes. The science of building and managing VOs is still being explored. There are many examples of early failures, and only a few examples that herald their potential success. Members of virtual organizations need to be sufficiently engaged to build collective intelligence. Take a look at the YouTube video and let me know what you think.