Abstract A 5‐year project to study scientific data uses in geography, starting in 1999, evolved into 20 years of research on data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. By emulating the “team science” approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. Building upon Paul N. Edwards's model of “making global data”—collecting signals via consistent methods, technologies, and policies—to “make data global”—comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. We reflect on continuity over generations of students and staff, transitions between grants, transfer of legacy data between software tools, research methods, and the role of professional data managers in the social sciences.

Abstract When developing university‐based research data curation services, libraries face critical decisions around organization and sustainability that can affect dataset producers' satisfaction with these services. We present a study, involving interviews (n = 43) and ethnographic observation, of how two libraries partnered with the Sloan Digital Sky Survey (SDSS) to curate a significant astronomy dataset. Each library took different decisions: one library assigned activities to a unit specializing in digital curation, while the other distributed activities across its existing units. Neither approach proved a silver bullet. While library staff members felt the outcomes largely met their expectations, SDSS leaders expressed mixed opinions. We identify three factors that contributed to these differences in perspective: differing strategic motivations for undertaking this Data Transfer Process, SDSS leaders' misperceptions about libraries, and organizational mismatches. These factors contributed to four differences in perspective between SDSS leaders and library staff: provenance as technical information or as information about social context, dataset as a live research object or as a static object to be preserved, systems and services tailored to the dataset or easily adaptable to other datasets, and obstacles as setbacks or as opportunities. Only those differences that emerged when SDSS collaboration members and library staff communicated frequently were resolved.

Enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the challenges of human interaction and retrieval. Data practices are local, varying from field to field, individual to individual, and country to country. As the number and variety of research partners expands, so do the difficulties of sharing, reusing, and sustaining access to data. Information retrieval is hindered by the lack of agreement on what are "data." Complexities of human interaction with data will be illustrated with empirical examples from environmental sciences, sensor networks, astronomy, biomedicine, and other fields. Unless larger questions of knowledge infrastructures and stewardship are addressed by research communities, "no data" often becomes the norm. Implications for policy and practice in the information sciences will be explored, drawing upon the presenter's book, Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press, 2015), and subsequent research.

Abstract University libraries are partnering with disciplinary data producers to provide long‐term digital curation of research data sets. Managing data set producer expectations and guiding future development of library services requires understanding the decisions libraries make about curatorial activities, why they make these decisions, and the effects on future data reuse. We present a study, comprising interviews (n = 43) and ethnographic observation, of two university libraries who partnered with the Sloan Digital Sky Survey (SDSS) collaboration to curate a significant astronomy data set. The two libraries made different choices of the materials to curate and associated services, which resulted in different reuse possibilities. Each of the libraries offered partial solutions to the SDSS leaders' objectives. The libraries' approaches to curation diverged due to contextual factors, notably the extant infrastructure at their disposal (including technical infrastructure, staff expertise, values and internal culture, and organizational structure). The Data Transfer Process case offers lessons in understanding how libraries choose curation paths and how these choices influence possibilities for data reuse. Outcomes may not match data producers' initial expectations but may create opportunities for reusing data in unexpected and beneficial ways.

Digital archives are the preferred means for open access to research data. They play essential roles in knowledge infrastructures—robust networks of people, artifacts, and institutions—but little is known about how they mediate information exchange between stakeholders. We open the “black box” of data archives by studying DANS, the Data Archiving and Networked Services institute of The Netherlands, which manages 50+ years of data from the social sciences, humanities, and other domains. Our interviews, weblogs, ethnography, and document analyses reveal that a few large contributors provide a steady flow of content, but most are academic researchers who submit data sets infrequently and often restrict access to their files. Consumers are a diverse group that overlaps minimally with contributors. Archivists devote about half their time to aiding contributors with curation processes and half to assisting consumers. Given the diversity and infrequency of usage, human assistance in curation and search remains essential. DANS' knowledge infrastructure encompasses public and private stakeholders who contribute, consume, harvest, and serve their data—many of whom did not exist at the time the DANS collections originated—reinforcing the need for continuous investment in digital data archives as their communities, technologies, and services evolve.

Open access to data is commonly required by funding agencies, journals, and public policy, despite the lack of agreement on the concept of "open data." We present findings from two longitudinal case studies of major scientific collaborations, the Sloan Digital Sky Survey in astronomy and the Center for Dark Energy Biosphere Investigations in deep subseafloor biosphere studies. These sites offer comparisons in rationales and policy interpretations of open data, which are shaped by their differing scientific objectives. While policy rationales and implementations shape infrastructures for scientific data, these rationales also are shaped by pre-existing infrastructure. Meanings of the term "open data" are contingent on project objectives and on the infrastructures to which they have access.

Author(s): Goodman, Alyssa; Pepe, Alberto; Blocker, Alexander W; Borgman, Christine L; Cranmer, Kyle; Crosas, Merce; Di Stefano, Rosanne; Gil, Yolanda; Groth, Paul; Hedstrom, Margaret; Hogg, David W; Kashyap, Vinay; Mahabal, Ashish; Siemiginowska, Aneta; Slavkovic, Aleksandra | Editor(s): Bourne, Philip E

Distributed sensing systems for studying scientific phenomena are critical applications of information technologies. By embedding computational intelligence in the environment of study, sensing systems allow researchers to study phenomena at spatial and temporal scales that were previously impossible to achieve. We present an ethnographic study of field research practices among researchers in the Center for Embedded Networked Sensing (CENS), a National Science Foundation Science & Technology Center devoted to developing wireless sensing systems for scientific and social applications. Using the concepts of boundary objects and trading zones, we trace the processes of collaborative research around sensor technology development and adoption within CENS. Over the 10-year lifespan of CENS, sensor technologies, sensor data, field research methods, and statistical expertise each emerged as boundary objects that were understood differently by the science and technology partners. We illustrate how sensing technologies were incompatible with field-based environmental research until researchers “unearthed” their infrastructures, explicitly reintroducing human skill and expertise into the data collection process and developing new collaborative languages that emphasized building dynamic sensing systems that addressed human needs. In collaborating around a dynamic sensing model, the sensing systems became embedded not in the environment of study, but in the practices of the scientists.

We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much‐improved data curation. (Hanson, Sugden, & Alberts, ) Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice.

Abstract In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI‐ORE) meets these requirements. We demonstrate a conceptual implementation of OAI‐ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multidisciplinary, multi‐university science and engineering research center, the Center for Embedded Networked Sensing.

Abstract ADEPT is a 5‐year project whose goals are to develop, deploy, and evaluate inquiry learning capabilities for the Alexandria Digital Library, an extant digital library of primary sources in geography. We interviewed nine geography faculty members who teach undergraduate courses about their information seeking for research and teaching and their use of information resources in teaching. These data were supplemented by interviews with four faculty members from another ADEPT study about the nature of knowledge in geography. Among our key findings are that geography faculty are more likely to encounter useful teaching resources while seeking research resources than vice versa, although the influence goes in both directions. Their greatest information needs are for research data, maps, and images. They desire better searching by concept or theme, in addition to searching by location and place name. They make extensive use of their own research resources in their teaching. Among the implications for functionality and architecture of geographic digital libraries for educational use are that personal digital libraries are essential, because individual faculty members have personalized approaches to selecting, collecting, and organizing teaching resources. Digital library services for research and teaching should include the ability to import content from common office software and to store content in standard formats that can be exported to other applications. Digital library services can facilitate sharing among faculty but cannot overcome barriers such as intellectual property rights, access to proprietary research data, or the desire of individuals to maintain control over their own resources. Faculty use of primary and secondary resources needs to be better understood if we are to design successful digital libraries for research and teaching.

We return to arguments made 10 years ago (Borgman, 1986a) that online catalogs are difficult to use because their design does not incorporate sufficient understanding of searching behavior. The earlier article examined studies of information retrieval system searching for their implications for online catalog design; this article examines the implications of card catalog design for online catalogs. With this analysis, we hope to contribute to a better understanding of user behavior and to lay to rest the card catalog design model for online catalogs. We discuss the problems with query matching systems, which were designed for skilled search intermediaries rather than end-users, and the knowledge and skills they require in the information-seeking process, illustrated with examples of searching card and online catalogs. Searching requires conceptual knowledge of the information retrieval process—translating an information need into a searchable query; semantic knowledge of how to implement a query in a given system—the how and when to use system features; and technical skills in executing the query—basic computing skills and the syntax of entering queries as specific search statements. In the short term, we can help make online catalogs easier to use through improved training and documentation that is based on information-seeking behavior, with the caveat that good training is not a substitute for good system design. Our long term goal should be to design intuitive systems that require a minimum of instruction. Given the complexity of the information retrieval problem and the limited capabilities of today's systems, we are far from achieving that goal. If libraries are to provide primary information services for the networked world, they need to put research results on the information-seeking process into practice in designing the next generation of online public access information retrieval systems. © 1996 John Wiley & Sons, Inc.

Searching information retrieval systems is a highly interactive, iterative process that cannot be understood simply by comparing the output of a search session (the “search product”) to a query stated in advance. In this article, we examine evaluation goals and methods for studying information retrieval behavior, drawing examples from our own research and that of others. We limit our review to research that employs online monitoring, also known as transaction log analysis. Online monitoring is one of few methods that can capture detailed data on the search process at a reasonable cost; these data can be used to build quantitative models or to support qualitative interpretations of quantitative results. Monitoring is a data collection technique rather than a research design, and can be employed in experimental or field studies, whether alone or combined with other data collection methods. Based on the research questions of interest, the researcher must determine what variables to collect from each data source, which to treat as independent variables to manipulate, and which to treat as dependent variables to observe effects. Studies of searching behavior often treat search task and searcher characteristics as independent variables and may manipulate other independent variables specific to the research questions addressed. Search outcomes, time, and search paths frequently are treated as dependent variables. We discuss each of these sets of variables, illustrating them with sample results from the literature and from our own research. Our examples are drawn from the Science Library Catalog project, a 7-year study of children's searching behavior on an experimental retrieval system. We close with a brief discussion of the implications of these results for the design of information retrieval systems. © 1996 John Wiley & Sons, Inc.

This study asks whether the disciplines of information science and communication are converging, as indicated by a bibliometric study of all core journals of both disciplines in the Social Sciences Citation Index (SSCI®) for the period 1977 to 1987. Results show very little convergence between these disciplines, at least on the basis of cross-disciplinary journal citation patterns, although the number of journals involved has increased slightly over time. A few journals are mainly responsible for the cross-disciplinary citing, and they are primarily information science journals citing communication journals. The results may be of interest to those studying scholarly communication or bibliometrics, to faculty constructing curricula in either of the disciplines, to communication and information science scholars seeking new areas of research, and to collection development librarians in drawing the boundaries of these disciplines. © 1992 John Wiley & Sons, Inc.

The study reported in this article was commissioned by the Getty Art History Information Program (AHIP) as a background investigation of personal name-matching programs in fields other than art history, for purposes of comparing them and their approaches with AHIP's Synoname™ project. We review techniques employed in a variety of applications, including art history, bibliography, genealogy, commerce, and government, providing a framework of personal name characteristics, factors in selecting matching techniques, and types of applications. Personal names, as data elements in information systems, vary for a wide range of legitimate reasons, including cultural and historical traditions, translation and transliteration, reporting and recording variations, as well as typographical and phonetic errors. Some matching applications seek to link variants, while others seek to correct errors. The choice of matching techniques will vary in the amount of domain knowledge about the names that is incorporated, the sources of data, and the human and computing resources required. Personal name-matching techniques may be included in name authority work, information retrieval, or duplicate detection, with some applications matching on name only, and others combining personal names with other data elements in record linkage techniques. We discuss both phonetic- and pattern-matching techniques, reviewing a range of implemented and proposed name-matching techniques in the context of these factors. © 1992 John Wiley & Sons, Inc.

We trained 40 doctoral students to search Inspec or ERIC on Dialog using either the Sci-Mate Menu or native commands. Each subject then performed a free search on his or her chosen research topic. In comparison with 20 control subjects—doctoral students for whom a free search was performed by a skilled librarian—the experimental subjects were no less satisfied with their retrievals, which were smaller but higher in precision than the retrievals produced by the intermediaries. End-users retrieved as many relevant references as the intermediaries. Use of the menu interface did not affect quality of retrieval or user satisfaction, although subjects instructed to use native commands required less training time, and interacted more with the databases than subjects trained on the Sci-Mate Menu. Inspec subjects placed a higher monetary value on their searches than did ERIC subjects, indicated that they would make more frequent uses of databases in the future, and interacted more with the database. Among the ERIC subjects, women made more errors than men, interacted more frequently with the database than men, placed a higher monetary value on their searches and indicated that they actually intended to consult a higher proportion of the references listed than men. © 1990 John Wiley & Sons, Inc.

We report on a two-year project funded by the United States Department of Energy (DOE) to develop a set of microcomputer-based training and assistance programs to support end user access to the Energy Database on the DOE information retrieval systems. We studied the information needs and information-seeking habits of energy researchers and then designed a set of programs tailored to their skill levels and needs. The software was developed in several iterations, with laboratory testing after each cycle. We learned that it was possible to construct a 10- to 15-minute instructional program and an automated assistance program that would allow most of the experimental users to conduct a reasonable search. However, the searches tended to be overly complex and problems with term selection remain. We discuss the issues in development, evaluation, and the study of user behavior in designing an interface tailored to a special population. © 1989 John Wiley & Sons, Inc.

The project Online Access to Knowledge (OAK) has developed a computer intermediary for selected users of the Department of Energy's DOE/RECON and BASIS online information retrieval systems. Its purpose is to enable people who have little or no training or experience in bibliographic searching to conduct their own searches, without the assistance of a trained librarian, hence permitting the user to work in both a place and time of his or her choosing. The purpose of this article is to report on the design and the rationale for the design. OAK software consists of both a tutorial and an assistance program. The latter does not employ a command language, hence obviates the need for a searcher to learn the formal language usually associated with an online database search service. It is central to our approach that this system does not supplant the user's ultimate primacy in knowing what he or she is looking for, nor in judging the results. © 1989 John Wiley & Sons, Inc.

The introduction of automated information retrieval (IR) systems was met with great enthusiasm and predictions that manual literature searching soon would be replaced. Three decades later, IR systems have not progressed to the stage where any but the dedicated few can operate them without a highly skilled human intermediary acting as interface between user and system. In the interim, we have learned that the retrieval process is extremely complex both in terms of understanding people and their communication and in terms of understanding scientific information and technical vocabulary. Experiments with new techniques suggest to many the possibility of eliminating the human intermediary, either in large part or altogether; others would argue that the retrieval problems are too complex to be resolved for more than highly restricted domains. The possibility of eliminating the human intermediary is of current research interest to the several disciplines that are represented on this panel.

Research in user behavior on online catalogs is in its early stages, but preliminary findings suggest that users encounter many of the same problems identified in behavioral studies of other types of bibliographic retrieval systems. Much can be learned from comparing the results of user behavior studies on these two types of systems. Research on user problems with both the mechanical aspects and the conceptual aspects of system use is reviewed, with the conclusion that more similarity exists across types of systems in conceptual than in mechanical problems. Also discussed are potential sources of the problems, due either to individual characteristics or to system variables. A series of research questions is proposed and a number of potential interim solutions are suggested for alleviating some of the problems encountered by users of information systems. © 1986 John Wiley & Sons, Inc.

An empirical study was performed to train naive subjects in the use of a prototype Boolean logic-based information retrieval system on a bibliographic database. Subjects were undergraduates with little or no prior computing experience. Subjects trained with a conceptual model of the system performed better than subjects trained with procedural instructions, but only on complex, problem-solving tasks. Performance was equal on simple tasks. Differences in patterns of interaction with the system (based on a stochastic process model) showed parallel results. Most subjects were able to articulate some description of the system's operation, but few articulated a model similar to the card catalog analogy provided in training. Eleven of 43 subjects were unable to achieve minimal competency in system use. The failure rate was equal between training conditions and genders; the only differences found between those passing and failing the benchmark test were academic major and in frequency of library use.

With the increasing number of information retrieval systems and databases available and the increasing demand of end users to utilize the systems, a need exists for improved interfaces and improved training mechanisms. This paper reports on a project to develop an integrated online instruction and assistance system to be used as a “front end” to the U.S. Department of Energy's RECON retrieval system. The conceptual framework for the interface design is based on individual characteristics of its current and prospective users, predominantly scientists conducting energy research. We are building a prototype based on information gained from interviews with scientists using the system (either directly or through a search intermediary) and interviews with search intermediaries. The paper reports on research in progress, including the results of the interviews and the preliminary design of the interface. The conference presentation will include a fuller description of the interface than can be specified here.

We report on a computer monitoring study of users of the Ohio State University Libraries' online catalog, an established and heavily used information retrieval system. To our knowledge, this is the first monitoring study of an online catalog performed without system-defined user sessions. Online catalogs represent a class of retrieval systems which are designed for end users, require little or no formal training, and replace an existing manual system. The study characterizes user behavior in terms of types of searches done, patterns of use, time spent on searching, errors, and system problems. Preliminary results suggest that users have much shorter sessions than on other types of retrieval systems. Patterns of use vary between campus libraries, academic quarters, and between short and long sessions. Results of the study will be applied to improving the user interface and other system features.

Abstract As computer‐based information retrieval and communication systems become more commonplace, researchers have a greater opportunity to evaluate the uses and impacts of new communication technologies. The systems and the kinds of data now available are discussed along with advantages and disadvantages of using computer‐monitored data.

No abstract available.