OCLC Research has done many studies of collective collections, nearly all of which focus on the collective holdings of a pre-defined group of institutions. For these analyses, the starting point is an enumeration of a group of institutions, and then a determination of what they collectively hold. This approach is quite useful when the purpose of the analysis is to inform decision-making on potential opportunities for collaboration within the group, such as shared print strategies or coordinated collection development. See, for example, our study of the 2016 Research Libraries UK collective collection, or our 2019 study of the Big Ten Academic Alliance collection. Let’s call collective collections of this kind group-focused collective collections.
The OCLC Research project Operationalizing the Art Research Collective Collection (OpArt) takes a different approach. Here, the starting point for our analysis is a collection of materials that we define as the art research collective collection – the holdings within the library community that are of interest to, support, and document art research. The general idea is that there is a corpus of materials supporting a particular discipline that is spread across the collections of many institutions. Let’s call collective collections of this kind discipline-focused collective collections.
Group- and discipline-focused analyses are two distinct approaches to collective collections. With one approach, we know the group of institutions and want to find out what they hold; with the other, we know the collection of materials and want to find out who holds them. From an operational standpoint, group-focused collective collections start with holdings information that allows you to gather bibliographic information on materials in the collection, while discipline-focused collective collections start with bibliographic criteria to identify materials of interest, which in turn allows you to recover holdings information on which institutions hold those materials in their local collections.
Discipline-focused collections aren’t easy to define
While group-focused collective collections are relatively straightforward to define – all you need is a list of institutions – discipline-focused collective collections present a greater challenge, both conceptually and operationally. In particular, the boundaries of a discipline-focused collective collection are not precise, because the boundaries of disciplines are themselves blurred and ever-shifting. While a group-focused collective collection might be likened to a box, precisely delineated, a discipline-focused collective collection would be better represented by a cloud, indistinct at the margins and evolving into new shapes over time.
Take for example, the notion of an art research collective collection: what are the boundaries of this collection? What kinds of material should be included, and what kinds are out of scope? Are there special material types that need to be included? And even if one can offer answers to these questions, issues arise when operationalizing them in library data: for example, which grouping of subject headings or classification numbers represent a comprehensive mapping to a particular disciplinary area? What bibliographic criteria adequately delineate special material types that are not formally defined in standard cataloging schema, and because of this, are subject to varying cataloging practices across institutions?
How to overcome these challenges? This was the question we faced with the OpArt project, where we wanted to construct and analyze a discipline-focused collective collection – specifically, the art research collective collection. Our solution was to adapt the group-focused approach to a discipline-focused collective collection analysis. We reasoned that one way to get a sense of what the art research collective collection looks like would be to select a group of institutions with an explicit mission to collect materials in support of art research, form the collective collection of this group, and examine its salient characteristics. We called this the proxy art research collective collection – a representation of what the broader, more conceptual art research collective collection might look like – and used this as the basis of our collective collection analysis for the OpArt project. So our discipline-focused collective collection is really an extrapolation from a group-focused collection. Although this approach has limitations, it worked well for our project; see our findings in the OCLC Research report Sustaining Art Research Collections: Using Data to Explore Collaboration.
Discipline-focused collections can be very important to analyze
Analysis of discipline-focused collections may become increasingly important as libraries seek new models for collecting, stewarding, and providing access to the scholarly record. One reason for this is that the discipline-focused view mirrors the one researchers take of library offerings in their scholarly area – they look for and access resources wherever they can get them to assemble what they need and rarely rely on just one library.
Another reason is that more and more of a given discipline-focused collective collection – what is effectively the scholarly record for that discipline – resides outside the local collection. We documented this trend nearly ten years ago in the OCLC Research report The Evolving Scholarly Record, where we made the argument that “[t]he increasing volume and complexity of the content potentially comprising the scholarly record, as well as a widening distribution of custodial responsibility, suggests that ‘local copies’ of the scholarly record are becoming increasingly partial—that is, the portion of the scholarly record that a single institution can hope to collect, store, and offer locally is getting smaller and smaller.”
As the scholarly record expands in size and scope, there are more opportunities for collecting in specialized subject areas, acquiring rare, archival, or “hyperlocal materials” (materials that for one reason or another are unique to a particular local collection), and preserving important outputs and byproducts of the research process (e.g., data sets, methodological tools, pre-prints). Many of these materials are intrinsically unique and therefore likely held by a single custodial steward. In these circumstances, the nature of the local collection changes: it becomes less a representative approximation of the scholarly record in a particular discipline, and more a relatively unique piece of a broader, networked collective collection, distributed across many institutions around the world.
A good example of this is the art research collective collection that we studied for the OpArt project. Recall that we worked with a very circumscribed proxy for this collection, based on the collective collection of 85 institutions known to focus their collecting in this area. In this analysis, we saw many features of a highly distributed, networked, discipline-focused collective collection. For example, the collection was distinguished by low overlap rates – three-quarters of the materials in the collection were held by a single group member. Beyond this, we found evidence of art libraries collecting heavily in categories of unique and rare material types, such as exhibition catalogs, auction catalogs, and artist files. Analysis of the subject headings in the collection suggests numerous examples of clusters of holdings in a broad range of fairly granular art-related sub-specialties like “Outdoor sculpture” and “Hand weaving.”
As the art research example suggests, a discipline-focused collective collection amplifies the importance of understanding the network context in which local collections are situated. Institutions may be stewarding materials that are a significant and unique component of a tacit collective collection supporting the research needs in a particular area. Gathering intelligence about that discipline-focused collective collection can aid local collection evaluation and decision-making. Key questions for discipline-focused collective collection analysis include:
- Boundaries: What kinds of materials are relevant to this collective collection? Which subject areas are most heavily collected? Are there special types of materials that are frequently used by scholars in this area?
- Network: Can a network of institutions be identified whose local collections are important contributors to the collective collection?
- Operationalization: What does analysis of the collective collection reveal about opportunities to operationalize it – that is, making it a practical reality, rather than just a construct in data?
Clarifying the nature of a discipline-focused collective collection helps to reveal pathways for improving the sustainability, discoverability, and accessibility of the materials in that collection. And a key pathway for achieving these ends is collaboration.
Collaborating around collective collections
A highly distributed, discipline-focused collective collection opens up opportunities for new kinds of partnerships among those institutions with a stake in its ongoing stewardship and accessibility. Indeed, this was the prime motivation behind the OpArt project: the need to secure the long-term sustainability of the art research collective collection, combined with the recognition that working together with other institutions toward that goal was a promising option.
The features of a discipline-focused collective collection often lend themselves to collaborative approaches. Consider this example. We mentioned earlier that the boundaries of a discipline-focused collective collection are blurred. The increasingly interdisciplinary nature of scholarly research stretches the scope of what a collection supporting research in a particular area needs to encompass. And these interdisciplinary needs can shift significantly over time as scholarly trends and interests evolve. There is also a need to understand broader societal contexts surrounding specialized research topics: for example, art exists within dynamic social, economic, technological, and political contexts that influence its nature and evolution. Consequently, specialized libraries like art libraries need access to a wide-ranging corpus of materials to adequately support the research needs of their patrons.
For many libraries, especially those that are small and/or under-resourced, it will not be feasible to collect extensively across the wide range of subjects pertinent to a particular discipline. So instead, they may partner with other libraries to gain access to those materials. We saw examples of this in our recent report Sustaining the Art Research Collection: Case Studies in Collaboration, where art libraries partnered with academic libraries in arrangements that included reciprocal borrowing privileges. It is important to emphasize reciprocal here: larger libraries with more general collections benefit from these collaborations by gaining access to the specialized holdings of institutions like art libraries – which might be of particular value to a university that is strengthening its academic offerings in disciplines like Art History.
How to collaborate around the collective collection
Effective, sustainable collaboration involving discipline-focused collective collections rests on network intelligence – reliable information about the contours and custodianship of the pool of materials around which collaborative activities are being formed. We have seen this with the OpArt project, where we used intelligence derived from collective collection analysis (as well as analysis of ILL data) to help define the boundaries of the art research collective collection, understand its salient features, and identify areas of potential collaboration for art libraries.
In an earlier report, OCLC Research, noting the changes in the evolution of the scholarly record, defined the concept of conscious coordination: a stewardship strategy of “deliberate engagement with—and growing dependence on—cooperative agreements, characterized by increased reliance on network intelligence (e.g., domain models, identifiers, ontologies, metadata) and global data networks.” The report goes on to observe that “[s]tewardship strategies based on conscious coordination involve an acceleration of an already perceptible transition away from relatively autonomous local collections to ones built on networks of cooperation across many organizations, within and outside the traditional cultural heritage community. In such an environment, providing local access to the scholarly record becomes less about accumulating large, representative local collections, and more about enabling access to scholarly resources distributed across the network.”
Conscious coordination is built on several key principles, one of which is broader awareness of system-wide context: “who is collecting what, what commitments have been made elsewhere in terms of stewarding various portions of the scholarly record, and how the local collection fits into the broader system-wide stewardship effort.” These are precisely the questions that often need to be answered when considering collaboration opportunities around a discipline-focused collective collection. Answering these questions with data-driven analytics helps libraries identify valuable collaborative opportunities, locate partners, and ultimately, make collaborations successful and sustainable. These data-driven analytics are an important aspect of the network intelligence mentioned above.
WorldCat: The intelligence in the network
OCLC’s WorldCat, the world’s most comprehensive database of information about library collections, is an invaluable source of the network intelligence that helps institutions understand the collections landscape – the system-wide context – in which they operate so they can make more informed decisions about local collections, as well as coalesce into mutually beneficial, sustainable partnerships. The OpArt project is an excellent illustration of network intelligence in action: we used WorldCat bibliographic and holdings information to define a representative art research collective collection, analyze its features, and highlight collaborative opportunities associated with it. WorldCat data even allowed us to sketch out a rough mapping of institutions contributing to the art research collective collection, and therefore candidate partners for stewardship-focused collaborations. In short, WorldCat provided the network intelligence to operationalize the principles of conscious coordination in the context of a discipline-focused art research collective collection.
As discipline-focused collective collections continue to grow in importance in the context of an increasingly distributed and globalized scholarly record, collaboration within networks of institutions will likewise become more important as a stewardship strategy. Network intelligence will be the fuel that drives these collaborations to success, by illuminating the opportunities for collective, coordinated action that build scale, reduce redundancy, and leverage complementarities. And WorldCat can be the leading source of that fuel, as the findings of the OpArt project illustrate.
Collective collection analysis, fueled by WorldCat data, can support many other kinds of library needs as well. For example, think about collaborations around shared offerings to support specific curricula; shared print programs that support the collection management lifecycle from accession to preservation; benchmarking metrics that indicate, for a given subject profile and network of institutions, points of comparison with which to identify local collection strengths. Network intelligence, derived from innovative uses of WorldCat data for collective collection analysis, can help unlock the rich collaborative possibilities open to libraries in these and other areas.
Check out all of OCLC Research’s work on collective collections, library collaboration, the scholarly record, evolving stewardship models, and much more!
Thanks to my colleagues Andy Breeding, Dennis Massie, Mercy Procaccini, and Chela Weber for their advice and suggestions for improving this post!
Brian Lavoie is a Research Scientist in OCLC Research. He has worked on projects in many areas, such as digital preservation, cooperative print management, and data-mining of bibliographic resources. He was a co-founder of the working group that developed the PREMIS Data Dictionary for preservation metadata, and served as co-chair of a US National Science Foundation blue-ribbon task force on economically sustainable digital preservation. Brian’s academic background is in economics; he has a Ph.D. in agricultural economics. Brian’s current research interests include stewardship of the evolving scholarly record, analysis of collective collections, and the system-wide organization of library resources.