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PurposeThe purpose of this paper is to develop some baseline data about games in libraries in North America. The term games is taken broadly in this piece to mean all types of games from card and board games to video games. The focus is primarily on public libraries, but there is some discussion of school and academic libraries as well.Design/methodology/approachThere were two surveys done. The first was a phone survey of 400 public libraries, selected at random. The second survey was a Web‐based convenience sample of libraries of different types. In both studies, we asked questions about the support of gaming in the library, the types of gaming programs run in the library, and the goals and outcomes of those gaming programs.FindingsAround 78 per cent of public libraries support gaming of some type. About 40 per cent run formal gaming programs, and about 20 per cent circulate games. The larger the library, the more likely they are to support gaming. The primary goals of gaming in libraries are to attract the underserved, attract current library patrons, and to create a space for social interactions between members of the community.Research limitations/implicationsThe first study is a random sample and therefore is a statistically significant representation of the population. The second study, being a Web‐based convenience sample, is not statistically representative of a population.Originality/valueThis type of baseline data is not available. Understanding how libraries are supporting games is valuable to researchers in asking appropriate questions. In addition, it helps libraries considering adding games to their services to learn how other libraries are doing it.

For decades, the corporate sector has exploited technological advances to better market and deliver products and services to customers via the techniques of data mining. The technique was not widely used in libraries. However, with the current emphasis on evidence-based decision making, libraries are beginning to utilize their system- and user- generated data. Data mining usually involves a significant endeavor to extract embedded and potentially useful information from large undiscovered data sets (Mitra & Acharya, 2003; Hand, Mannila & Smyth, 2001; Frawley, Piatetsky-Shapiro, & Matheus 1992; Piatetsky-Shapiro & Frawley 1991). These data mining techniques are being used by librarians to improve both internal decision-making and external user services by extracting information from operational datasets of both bibliographic and user data. OCLC Research has taken advantage of the WorldCat database, which includes more than 95 million bibliographic records and 1.2 billion holdings records, as well as data provided by other major library systems and consortia to develop user-oriented collections and services (http://www.oclc.org/research/projects/mining/).

One of the valuable offerings of librarians in the digital age is the human intermediation of information needs. In physical libraries, these reference questions are answered, and few artifacts remain from the transaction; therefore, the knowledge created through the work of the librarian leaves with the patron. Due to the medium of communication, digital reference transactions capture the knowledge of information professionals. There are hundreds of digital reference services generating knowledge every day; however, the lack of a schema for archiving reference transactions from multiple services makes it difficult to create a fielded, searchable knowledge base. The development of such a schema would allow researchers to develop tools that practitioners can employ. In turn, this would create a collaborative environment for digital reference evaluation. The goal of this work is to outline the steps needed to develop this schema, present the results of a survey of digital reference services, explore some of the pitfalls in the process, and envision the future uses of this Digital Reference Electronic Warehouse.

Over the past few years, data mining has moved from corporations to other organizations. This paper looks at the integration of data mining in digital library services. First, bibliomining, or the combination of bibliometrics and data mining techniques to understand library services, is defined and the concept explored. Second, the conceptual frameworks for bibliomining from the viewpoint of the library decision-maker and the library researcher are presented and compared. Finally, a research agenda to resolve many of the common bibliomining issues and to move the field forward in a mindful manner is developed. The result is not only a roadmap for understanding the integration of data mining in digital library services, but also a template for other cross-discipline data mining researchers to follow for systematic exploration in their own subject domains.

Archaeologists have used material artifacts found in a physical space to gain an understanding about the people who occupied that space. Likewise, as users wander through a digital library, they leave behind data‐based artifacts of their activity in the virtual space. Digital library archaeologists can gather these artifacts and employ inductive techniques, such as bibliomining, to create generalizations. These generalizations are the basis for hypotheses, which are tested to gain understanding about library services and users. In this article, the development of traditional archaeological methods is presented and used to create a conceptual framework for the artifact‐based evaluation in digital libraries.

While a growing number of the digital reference services in libraries have become part of collaborative reference networks, other entities that serve similar information-seeking needs such as special collections and museums have not joined these networks, even though they are answering an increasing number of questions from off-site patrons via the Internet. This article examines the differences between questions asked electronically of traditional reference services and those asked of special collections services; it further explores how a better understanding of digital reference in special collections will facilitate the development of the tools and models needed to create a bridge between digital human intermediation at general academic libraries, special collections, and museums.

This article describes a Delphi study conducted to determine factors that affect the process of routing and assigning reference questions received electronically by digital reference services, both to experts within the service and between services. Fifteen factors were determined, by expert consensus, to be important at the conclusion of this study. These fifteen factors are divided into three groups: (1) general factors, (2) factors when routing the question to an individual, and (3) factors when routing the question to another service. These factors were ranked in order of importance and grouped according to the recipient of the question. These fifteen factors need to be taken into account when automating the triage process. This article has laid out a methodology for investigating other digital reference processes so that those processes amenable to automation may be automated, and experts' talents and time may be best used.

SUMMARY Ambiguities in Web search tool (more commonly known as “search engine”) terminology are problematic when conducting precise, replicable research or when teaching others to use search tools. Standardized terminology would enable Web searchers to be aware of subtle differences between Web search tools and the implications of these for searching. A categorization and nomenclature for standardized classifications of different aspects of Web search tools is proposed, and advantages and disadvantages of using tools in each category are discussed.

The Digital Reference Electronic Warehouse (DREW) project is a collection of digital reference transactions from different services and different communication channels that live in a single space. Reference services work with DREW to submit transactions using the DREW schema, which is conceptually similar to the MARC record format for bibliographic materials. Researchers can then receive records from DREW to improve our knowledge of digital reference. These researchers then use the results of their research to create tools, reports, and models based on the DREW schema, and place those items into a management information system (MIS). The services can then access the MIS and apply those tools to their own archives. The result is that services can benefit directly and rapidly from research, and are then more likely to continue their involvement with the project. This infrastructure creates a collaborative space where researchers and practitioners can benefit from the work of each other and aid us in advancing the field of digital reference.

Archeologists use artifacts to make statements about occupants of a physical space. Users of information resources leave behind data–based artifacts when they interact with a digital library or other Web–based information space. One process for examining these patterns is bibliomining, or the combination of data warehousing, data mining and bibliometrics to understand connections and patterns between works. The purpose of this paper is to use a research framework from archeology to structure exploration of these data artifacts through bibliomining to aid managers of digital libraries and other Web–based information resources.