6.1 Current Models
An underlying assumption of this study was that centers could be categorized by models of governance (e.g., membership, consortia, independents, university). However, upon closer analysis, this assumption proves difficult to substantiate because of all the exceptions. Two membership-based centers, for example, are governed in whole or in part by a parent university. Some centers still managed by their founders reside in university environments and rely on university resources but apparently operate independently of any overt university governance (oversight is vested in the founders). Another center has strong programmatic and in-kind support from a university, but declares itself “independent” of its governance and oversight.
In sum, governance as a model is too fluid for reliably characterizing the centers in this survey. Funding models also fall short. With one exception (a center funded in its entirety by a single philanthropy), the centers are funded by a diverse and changing mix of support that relies greatly on universities and funding agencies or foundations (see Section 4.5.3).
How, then, can DHCs be categorized? When all the considerations of governance, administration, and operation are considered, the real distinction lies in the focus of the center. The two clear divisions are as follows:
- Resource focused. Centers are organized around a primary resource, located in a virtual space, that serves a specific group of members. All programs and products flow from the resource, and individual and organizational members help sustain the resource by providing content, and, in some instances, volunteer labor.
- Center focused. Centers are organized around a physical location, with many diverse projects, programs, and activities that are undertaken by faculty, researchers, and students, and that offer many different resources to diverse audiences. Most of the centers surveyed operate under this model.
HASTAC is an outlier in this discussion. It may be an emerging hybrid between the two models outlined above, in that it pursues diverse projects and programs but is membership based and operates largely in a virtual space.
6.2 Benefits and Limitations of Center- and Resource-Focused Models
The two models that emerge from this analysis have strengths and weaknesses in their respective approaches. Digital humanities centers with a center-based focus can respond quickly and independently to changes in operations and programs because decision making is centralized. These centers are more agile and can experiment and take risks. Their diversified program base means that an unpromising program can be dropped without compromising the center or its other activities. Their physical presence also allows these centers to interact and develop resources with their local communities.
However, the number of activities undertaken by these centers results in a plethora of resources that must be independently maintained and managed. Expertise is dispersed among many projects, to the possible detriment of individual projects. If the center is disbanded, projects without external PI support or a user base willing to sustain the resource risk being orphaned.
Resource-focused centers leverage the knowledge, efforts, and shared interests of their members to create a resource that is beneficial to the entire member community. The resource is built by members who provide content and, in some instances, volunteer services, while the center supports the infrastructure and coordinates, maintains, and makes the resource accessible. Efficiencies exist in areas of content creation and compilation, shared member expertise, and management and sustainability of the resource.
But resource-focused centers also come with compromises. They may not be as agile as other centers and may be more risk averse in their decision making because any change in the operation of the resource directly affects tens of thousands of members. They also may have a hierarchy of member committees or groups that must be contacted before a decision can be made.
In addition, resource-focused centers vest considerable efforts in their startup phase, as they concentrate on compiling a critical mass of content to make the resource valuable and, on front-end systems, accessible. Since the resource is the center’s raison d’être, any problems in this early phase can be extremely risky for the center: everything depends on the resource gaining traction.
6.3 Current Models and the Changing Nature of Humanities Scholarship
Both center- and resource-focused models are addressing the changing nature of humanities scholarship by building digital collections and tools to make research more efficient and by exploring different approaches to humanities research. However, some features of these centers may inadvertently hinder wider research and scholarship.
First, the silo-like operation of current centers favors individual projects that are not linked to larger digital resources that would make them more widely known within the research community. When one examines the projects of the 32 surveyed centers en masse, one finds hundreds of projects of potential interest to larger communities that are little known outside the environs of the center and its partners. Moreover, in the absence of preservation plans, many of these projects risk being orphaned over time, as staff, funding, and programming priorities change. In the absence of repositories that enable greater exposure and long-term access, the current landscape of many silo-like centers results in unfettered and untethered digital production that will be detrimental to humanities scholarship.
The silo-like nature of centers also results in overlapping agendas and activities, particularly in areas of training, digitization of collections, and metadata development. With centers competing for the same limited funding pool, they can ill afford to continue with redundant efforts.
The form of collaboration that takes place in today’s centers is also inadequate for future scholarship. The differences between the small-scale, narrowly focused collaborations common among DHCs, and the more coordinated, large-scale organizational collaborations characteristic of regional and national centers are more than just differences in size and degree. They involve wholly new processes of management, communication, and interaction.
Of late, a handful of centers are embarking on collaborations that address broader, community-wide issues (such as preserving virtual worlds and strategies for managing born-digital materials). Whether these efforts will move centers toward larger-scale models of collaboration or result in new types of centers is uncertain. However, it is these larger scale efforts, which effectively leverage resources in the community to address broader issues of cyberinfrastructure, that have been missing from the digital humanities scene and that will be necessary to support future humanities research.
6.4 Collaborative Aspects Critical to the Success of Regional or National Centers
As digital humanities computing becomes an integrative, multi-team endeavor, the motivations, support structures, and reward systems that make for successful collaboration become critically important. What aspects of collaboration may be critical to the success of regional or national centers? When the current DHC collaborative landscape is considered in light of successful national collaborations in the scientific community, the following characteristics emerge as particularly important.
Compelling, Community-Wide Research Needs
Digital humanities scholarship thrives on the investigation of research questions both large and small, but it is the former that is the better candidate for regional and national centers. Recent collaborative efforts focusing on digital preservation issues (cited above) offer one example of a “big” problem amenable to a large-scale collaboration. Other compelling research needs might coalesce around cyberinfrastructure that supports digital humanities scholarship, such as sharing advanced computing infrastructure, training in advanced technologies for humanities research, and developing repositories for digital collections.
Larger regional and national efforts may also coalesce around humanities research problems that cut across disciplinary communities. The Pleiades Project, for example, addresses a long-standing need among classicists, archaeologists, historians, literary scholars, and other humanists for a reliable, up-to-date reference for ancient geography. Its large-scale, cross-disciplinary effort may well establish it as a de facto “national” center for the study of ancient geography.
No Center Left Behind
The current (and currently proliferating) landscape is one of individual centers pursuing separate research agendas. These centers have significant professional interests vested in them and considerable amounts of human, financial, and technical infrastructure that is unlikely to be relinquished in deference to other models. Equally important, the centers believe deeply in the value and success of their efforts. Given these circumstances, some DHCs voiced uncertainty about the need for national and regional models, wondering about their purpose, intent, and structure.
Implicit in their concern is the need for clarification of the role of individual DHCs in the context of regional and national centers. Digital humanities centers are a locus of activity that is valued by universities, researchers, faculty, and students. If regional and national models are to be viable, they will need to draw on the individuals and expertise resident in current centers. All parties need greater clarity about the roles for different types of centers (local, regional, and national), as well as strategies for inclusion and interaction among them.
Trust as the Tie that Binds
Academic tenure-and-review committees have long been accused of failing to give credence to digital scholarship. Michael Shanks, codirector of the Stanford Humanities Lab, believes the reason for their hesitation is rooted in trust. These committees want to know if an individual on a team has done the work, or if he or she is simply riding on someone else’s coattails.
Shanks (2008) suggests that if collaborative work in the digital humanities moves into what he calls established “laboratories,” collaboration will become associated with “continuity, community, and reputation.”
An established lab has a history independent of its members. A track record will establish a reputation that facilitates trust in the collaborative success of the lab-that people there genuinely work together. So when a new joint publication is produced, it will be far easier to associate individual effort and talent with that of the group-individual scholarship gaining credit from its location within a discipline that is precisely identified with its peer practitioners and community.
A shift toward this evaluative framework-one that invests a level of trust in the work of the center and reflects that onto individuals-is needed in the humanities if humanists are to put significant efforts into the collaborative activities of regional and national centers.
Acceptance by the academy is important to humanists, but for some collaborations it is not enough to guarantee success. Collaborations involving contributions to a community resource often require other reward systems and incentives to help the resource reach a critical mass and to keep it current and relevant to the community.
The ArchNet project team, for example, found that participant contributions were less than expected several years into the project. They suspect that feedback with their membership (scholars, architects, students, and urban planners interested in Islamic culture) is more critical to participation than realized, and that reward systems that enhance the personal reputation of contributors are important. MERLOT offers such rewards to its contributors by means of a multitiered system that includes recognition for exemplary contributions, various service awards, and a peer-review system that rates contributions. Equally important, MERLOT users (higher education faculty and instructors, middle and high school teachers, librarians) offer additional “social rewards”: they comment, rate, and incorporate contributions into their personal teaching collections. These activities indicate peer recognition (through use) that enhances a contributor’s reputation.
In the sciences, motivating forces take a different form. A study of data contributions to genetics databases revealed that the primary motivation came from two external sources: leading scholarly journals and funding agencies that require data deposition as a prerequisite to publication (for the former) and as a condition of a grant award (for the latter). Altruistic reasons, while less common, were also a source of motivation: contributions were often made out of a sense of obligation to the community or a desire to contribute to a valuable resource.
For national and regional DHCs that emerge around a data resource, identifying motivations and incentives is critical. Some of the more forceful measures (funder-mandated contributions) may have a role, while others (prerequisite for publication) may not. The spirit of sharing and openness that characterizes humanities research must be realistically balanced with professional incentives and opportunities.
The Nature of the Work
Studies on scientific collaborations are abundant, and much of what has been reported mirrors what the centers themselves describe as important characteristics of partnerships (see 4.6.3). However, the traits articulated by DHCs focus on the partner and the process, while studies in the literature also consider how the nature of the work may be related to the success of a collaboration.
A recent study of more than 200 scientific collaboratories suggests that successful large-scale collaborations occur most frequently when the work is easily divided into components rather than “tightly coupled.” Even in an age of instantaneous and ubiquitous communication mechanisms, highly integrated projects apparently require the frequent and often innocuous interactions (such as hallway conversations) that occur when collaborators are co-located rather than geographically dispersed.
Studies also show that collaborations organized around the sharing of data or tools are easier to accomplish than are those organized around the sharing of knowledge. Similarly, projects involving aggregation of resources are easier to develop than projects involving co-creation of resources. These findings may be related to the notion about loosely coupled versus tightly coupled projects, but they also likely reflect the belief that it is easier to transmit information than knowledge.
6.5 Some Science Models for Consideration
As part of a large National Science Foundation-funded study of collaboratories, Bos et al. (2007) created a typology of collaboratories based on organizational patterns found in existing large-scale scientific collaborations. Because these authors employed a bottom-up methodology designed to help those who are developing new collaborations, their findings are particularly relevant when considering the types of regional and national centers that might be developed in the humanities.
The classification system developed by Bos and his colleagues is based largely on the goals inherent in existing collaborations. Some of these same collaboratory types already exist in the humanities on a small scale; others are found in community-based projects of interest to the humanities. The classifications defined by Bos et al. are as follows:
- A Shared Instrument Collaboratory provides remote access to large, expensive scientific instruments. These types of collaborations are prevalent among astronomers, who need access to large telescopes, and among physicists, who need access to particle accelerators. This model may be relevant for humanists who need access to supercomputers for advanced computational work.
- A Community Data Systems Collaboratory is a semipublic (i.e., open to the profession) information resource created, maintained, or enhanced by a geographically distributed community. Well-known biology databases such as the Protein Databank and GenBank are organized as these types of collaborations. In the humanities, the Pleiades Project may be the closest manifestation of this model, although it shares some aspects of the Open Community Contribution System model (below) as well.
- An Open Community Contribution System aggregates the efforts of many geographically dispersed individuals toward a common research problem. A project that parallels this model in broad strokes is the Library of Congress (LC)/Flickr Commons collaboration, in which the collective knowledge of the public is used to enhance cataloging and metadata of LC images via social-networking mechanisms.
- A Virtual Community of Practice is a community of individuals who share a research interest and communicate about it online. The community does not undertake joint projects, but it does share professional information, advice, techniques, and contacts. The humanities have many examples of collaborations of this sort, one of the most prominent being H-NET.
- A Virtual Learning Community is a community brought together to increase the knowledge of its participants through formal learning programs (not through original research). These communities are often affiliated with degree-granting programs, but they may also be organized around professional development opportunities. For example, a national or regional training center that focused on digital technologies for humanities research would constitute a virtual learning community collaboratory.
- A Distributed Research Center is a virtual version of a university research center. This type of collaboratory joins the expertise, resources, and efforts of many individuals interested in a topical area, and conducts joint projects in that area.
- A Community Infrastructure Project focuses on developing infrastructure (i.e., tools, protocols, access methods) to further work in a particular domain. The Internet Archive models this type of collaboratory by bringing together efforts of individuals, information science professionals, technologists, and cultural heritage institutions to create an infrastructure for archiving Web and multimedia resources for research.
In looking for collaborative structures that can address the changing needs of humanities scholarship, the models employed by the sciences, which Bos summarizes in the above typology, offer a starting point for discussion. Copious research has been done on these collaborations, particularly on the organizational structures and behaviors that affect their success. As the humanities community considers next steps for the development of digital humanities centers, it might investigate these organizational and social factors more closely and apply their lessons within the context of the humanities.