Scholarship in the Digital Age: Information, Infrastructure, and the Internet. By Christine L. Borgman. Cambridge, MA: MIT Press, 2007. Pp. xxiv+336. $35.00 (cloth). ISBN‐13 978‐0‐262‐02619‐2.

PREFACE The growth in the capacity of the research community to collect and distribute data presents huge opportunities. It is already transforming old methods of scientific research and permitting the creation of new ones. However, the exploitation of these opportunities depends upon more than computing power, storage, and network connectivity. Among the promises of our growing universe of online digital data are the ability to integrate data into new forms of scholarly publishing to allow peer-examination and review of conclusions or analysis of experimental and observational data and the ability for subsequent researchers to make new analyses of the same data, including their combination with other data sets and uses that may have been unanticipated by the original producer or collector. The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented. Recognizing the needs for better data referencing and citation practices and investing effort to address those needs has come at different rates in different fields and disciplines. As competing conventions and practices emerge in separate communities, inconsistencies and incompatibilities can interfere with promoting the sharing and use of research data. In order to reconcile this problem, sharing experiences across communities may be necessary, or at least helpful, to achieving the full potential of published data. Practical and consistent data citation standards and practices are thus important for providing the incentives, recognition, and rewards that foster scientific progress. New requirements from funding agencies to develop data management plans emphasize the need to develop standards and data citation practices. Together with representatives from several other organizations, the CODATA-ICSTI Task Group examines a number of key issues related to data identification, attribution, citation, and linking. Additionally, the Task Group helps coordinate international activities in this area and …

OUT OF CITE, OUT OF MIND: THE CURRENT STATE OF PRACTICE, POLICY, AND TECHNOLOGY FOR THE CITATION OF DATA CODATA-ICSTI Task Group on Data Citation Standards and Practices

Much of the recent research on digital data repositories has focused on assessing either the trustworthiness of the repository or quantifying the frequency of data reuse. Satisfaction with the data reuse experience, however, has not been widely studied. Drawing from the information systems and information science literature, we developed a model to examine the relationship between data quality and data reusers' satisfaction. Based on a survey of 1,480 journal article authors who cited Inter-University Consortium for Political and Social Research ICPSR data in published papers from 2008-2012, we found several data quality attributes-completeness, accessibility, ease of operation, and credibility-had significant positive associations with data reusers' satisfaction. There was also a significant positive relationship between documentation quality and data reusers' satisfaction.

/pdf/social-scientists-satisfaction-with-data-reuse-aonl1hug1k.pdf

Social scientists' satisfaction with data reuse

The value of sharing scientific research data is widely appreciated, but factors that hinder or prompt the reuse of data remain poorly understood. Using the Theory of Reasoned Action, we test the relationship between the beliefs and attitudes of scientists towards data reuse, and their self-reported data reuse behaviour. To do so, we used existing responses to selected questions from a worldwide survey of scientists developed and administered by the DataONE Usability and Assessment Working Group (thus practicing data reuse ourselves). Results show that the perceived efficacy and efficiency of data reuse are strong predictors of reuse behaviour, and that the perceived importance of data reuse corresponds to greater reuse. Expressed lack of trust in existing data and perceived norms against data reuse were not found to be major impediments for reuse contrary to our expectations. We found that reported use of models and remotely-sensed data was associated with greater reuse. The results suggest that data reuse would be encouraged and normalized by demonstration of its value. We offer some theoretical and practical suggestions that could help to legitimize investment and policies in favor of data sharing.

/pdf/attitudes-and-norms-affecting-scientists-data-reuse-31bgzac7gr.pdf

Attitudes and norms affecting scientists' data reuse.

Tuomi, Ilkka: Corporate Knowledge. Theory and Practice of Intelligent Organizations Metaxis Helsinki, 1999 Around ten years of research discussing resource knowledge and its management show us that we do not understand the process of knowledge creation in organisations sufficiently. Still after this intensive period, we find that knowledge management projects in companies often fail; even company consultants only claim to achieve 25 percent success in projects. Most misleading are knowledge management projects with a high orientation on IT. Even the new combination of knowledge instruments nor the introduction of incentive systems could help to overcome the disadvantageous effects of the first and second generation of knowledge management (distinction based on Tuomi 2002), which were AI-inspired or based on information systems using contextual information respectively. From this viewpoint, Tuomi's theoretical ideas are still up to date. Published in 1999, Tuomi's dissertation starts with the question: `What do we understand of the limitations and problems of common sense concepts of information and knowledge, and do these limitations have practical implications in everyday organizational life?' Obviously, we do not understand enough. According to Tuomi, the following indications back up this assumption: First, knowledge management is often seen as a technological issue. Against this, Tuomi emphasises that technology is a relatively small part of any successful knowledge management program. It is still not unusual that `information is often produced without any clear model of why someone would need it, and technology gets too much attention compared to organizational practice'. This leads to Tuomi's second indication, that tools and technologies cannot be utilised without a corresponding practice. In this view, it is not essential that single individuals know and act based on their knowledge. A conceptualisation of knowledge in organisations has to emphasise the link between knowledge and action as the basic constraint of social systems. Knowledge in organisations - corporate knowledge - is socially and culturally embedded, and it can only be generated through changes in organisational activities and practices. Third, Tuomi argues, `that researchers often have been too quick in pointing out that organizations don't have real memory, sensemaking capability and intelligence, and that, of course, human beings are the unique hosts of these cognitive faculties.' The central idea of Tuomi's book the 5-A model of organisational knowledge generation deals with the concept that organisations are collective entities where it is possible to find similarities to intelligence as manifested in humans. With Corporate Knowledge - Theory and Practice of Intelligent OrganiZations, Tuomi prepares the theoretical groundwork for the third generation of knowledge management (Tuomi 2002) that links knowledge and action/practice to a more effective access to information. Consequently, Tuomi pursues questions concerning what role information systems play in knowledge management; how people create shared understandings about the world; what theoretical approaches enable us to understand how to connect information and communication into action; and how organisational knowledge actually emerges. It is interesting to read that these questions emerge from the knowledge management project `Future Watch' at Nokia Research Center and Nokia Telecommunications that failed in the early 1990s. To build up an alternative perspective, in part II Tuomi presents and compares current conceptualisations of knowledge and knowing in organizations: (1) the `prominent empiristic and positivistic view' represented by Bertrand Russell and (2) the `constructivistic and phenomenological view' represented by Henri Bergson (based on Vygotsky). With these authors he contrasted two opposite epistemologies: Russell understands the `human mind as an invariant intelligent faculty' and investigates objects, representations and the logic of thought in a positivistic tradition. …

Corporate Knowledge. Theory and Practice of Intelligent Organizations

This overview is a study of the methods used at a variety of universities, and international government libraries and archives, to select, acquire, describe and access web resources for their archives. Creating a web archive presents many challenges, and library and information schools should ensure that instruction in web archiving methods and skills is made part of their curricula, to help future practitioners meet those challenges. In preparation for developing a web archiving course, the author conducted a comprehensive literature review. The findings are reported in this paper, along with the author's views on some of the methods in use, such as how traditional archive management concepts and theories can be applied to the organization and description of archived web resources.

/pdf/an-overview-of-web-archiving-12znxlj8ha.pdf

An Overview of Web Archiving

Information technology and data sharing policies have made more and more social science data available for secondary analysis. In secondary data analysis, documentation plays a critical role in transferring knowledge about data from data producers to secondary users. Despite its importance, documentation of social science data has rarely been the focus of existing studies. In this paper, based on an introduction of the concept of documentation and its role in secondary data analysis, the authors proposed the Documentation Evaluation Model(DEM) for social science data. In the model, two indicators are used to evaluate the documentation for social science data: sufficiency and ease-of-use. Then the authors review the sufficiency problems of documentation, identify three factors that affect the sufficiency of documentation: users, data, and the ease-of-use of documentation, and formulate hypotheses about how those factors affect the sufficiency of documentation. In future research, a survey instrument will be created based on the model and the factors affecting the sufficiency of documentation. The survey instrument will then be applied to the secondary users of social science data. Hypotheses will be tested based on the survey data.

/pdf/documentation-evaluation-model-for-social-science-data-3cpq2y8jp9.pdf

Documentation evaluation model for social science data

This article presents a conceptual framework for library name authority control, including methods for disambiguating agents that share the same name and for collocating works of agents who use multiple names It then discusses the identifier solutions tried or proposed in the library community for name authority control, analyzes the various identity management systems emerging outside of the library community, and envisions future trends in name authority control

Evolving Landscape in Name Authority Control

Secondary data users need three types of knowledge to analyze secondary data: knowledge about data, background knowledge necessary to understand and interpret data, and data analysis skills. Part of knowledge about data is provided by the documentation of data. Background knowledge and data analysis skills are internalized as users' absorptive capacity. When documentation and their absorptive capacity are inadequate, users need to seek outside information to use secondary data. In this paper, causes of inadequate documentation were analyzed, why and how secondary users seek outside information were reported. Then based on the findings, implications about how to facilitate secondary data use were discussed.

https://asistdl.onlinelibrary.wiley.com/doi/pdf/10.1002/meet.2009.145046024

Overcoming inadequate documentation

This paper presents results from a survey of researchers’ behavior and attitudes about depositing data from sponsored research. The survey was conducted as part of a larger project called “Incentives for Data Producers to Create ‘Archive-Ready’ Data.1 “Archive-ready data” are data that meet the minimum requirements for data quality, metadata, and documentation of the repository or archives where they will be preserved. We found that researchers often are unaware of data deposit requirements, but that they would be more willing to deposit “archive-ready” data if they knew it would be used and have a broader public benefit. Our research has identified barriers that data producers face when preparing data for deposit in an archives. We discuss broader implications of the findings for data producers and archivists in a variety of different settings and suggest ways the archivists and records managers might use incentives to encourage data producers to create “archive-ready” data.

Jinfang Niu

Papers

An Overview of Web Archiving

Documentation evaluation model for social science data

Evolving Landscape in Name Authority Control

Overcoming inadequate documentation

Incentives for Data Producers to Create "Archive-Ready" Data: Implications for Archives and Records Management