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The purpose of this paper is to demonstrate how knowledge of local research data management (RDM) practices critically informs the progressive development of research data services (RDS) after basic services have already been established.

An online survey was distributed via e-mail to all university faculty in the fall of 2013, and was left open for just over one month. The authors sent two reminder e-mails before closing the survey. Survey data were downloaded from Qualtrics survey software and analyzed in R.

In this paper, the authors reviewed a subset of survey findings that included data types, volume, and storage locations, RDM roles and responsibilities, and metadata practices. The authors found that Oregon State University (OSU) researchers are generating a wide variety of data types, and that practices vary between colleges. The authors discovered that faculty are not utilizing campus-wide storage infrastructure, and are maintaining their own storage servers in surprising numbers. Faculty-level research assistants perform the majority of data-related tasks at OSU, with the exception of data sharing, which is primarily handled by the professorial ranks. The authors found that many faculty on campus are creating metadata, but that there is a need to provide support in how to discover and create standardized metadata.

This paper presents a novel example of how to efficiently move from establishing basic RDM services to providing more focussed services that meet specific local needs. It provides an approach for others to follow when tackling the difficult question of, “What next?” with regard to providing academic RDS.

This chapter introduces the Person-in-Environment (PIE) framework, a research design and a nationwide empirical study, developed by the author, to measure the relative impacts of socio-structural and personal factors on individual-level information behaviours (IB) and outcomes. The IB field needs to tackle two questions: (1) In a particular situation, how much of an individual's IB is influenced by personal characteristics? and (2) How much of this behaviour is shaped by one's environment, such as socio-structural barriers? PIE is a beginning effort to address this agency–structure debate, which is a topic that confronts many social scientists. This chapter first outlines IB research relevant to agency–structure integration. It then presents six principles of the PIE framework. Personal characteristics (e.g. cognitive and affective factors) and socio-structural factors (e.g. information resources distribution) are conceptualised as interrelated. Thus, these need to be tested simultaneously. Previously, it was difficult to link individual- and societal-level datasets because their units of observation often vary. To overcome these methodological challenges, this author purposed a research design that employs secondary analysis, geographic information systems techniques and structural equation modelling. An empirical study of the library usage by 13,000 American 12th graders is presented to demonstrate PIE's applicability. Discussions on the future directions of PIE studies conclude the chapter. The PIE framework can contribute to conceptual and methodological development in IB research. It also offers scholars and policymakers a way to empirically assess the contributions of information services on an individual's life, while taking personal differences into account.

This study seeks to apply ecological psychology's concept of “affordance” to graduate students' information behavior in the academic library, and to explore the extent to which the affordances experienced by graduate students differed from the affordances librarians were attempting to provide.

In‐depth, qualitative interviews with graduate students and academic librarians explored how the students perceived and used the library's various “opportunities for action” (e.g. books, databases, instructional sessions, librarians, physical space, etc.) and compared these perceptions and behavior with librarians' intentions and expectations.

Findings indicate a disparity between expectations and experience and point to graduate students as an underserved population in this context, especially in terms of the library's outreach efforts. In addition, because graduate students are increasingly teaching introductory undergraduate courses, communication methods that bypass graduate students tend to miss undergraduate students as well.

Practical implications discussed in this paper include possible methods of improving communication channels between graduate students and academic librarians, and considerations for information literacy instruction.

This paper presents a unique perspective by using affordance theory to frame students and librarians' expectations about library services. The findings are particularly valuable for their implications for library‐patron communication and information literacy.

The purpose of this article is to alert researchers to software for web tracking of information seeking behaviour, and to offer a list of criteria that will make it easier to select software. A selection of research projects based on web tracking as well as the benefits and disadvantages of web tracking are also explored.

An overview of the literature, including clarification of key concepts, a brief overview of studies of web information seeking behaviour based on web tracking, identification of software used, as well as the strengths and short‐comings noted for web tracking is used as a background to the identification of criteria for the selection of web tracking software.

Web tracking can offer very valuable information for the development of websites, portals, digital libraries, etc. It, however, needs to be supplemented by qualitative studies, and researchers need to ensure that the tracking software will collect the data required.

The criteria is not applied to any software in particular.

The criteria can be used by researchers working on web usage and web information seeking behaviour to select suitable tracking software.

Although there are many reports on the use of web tracking (also reported in this article), nothing could be traced on criteria for the evaluation of web tracking software.