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Although a substantial corpus of digital materials is now available to scholarship across the disciplines, objective evidence of their use, impact, and value, based on a robust assessment, is sparse. Traditional methods of assessment of impact in the humanities, notably citation in scholarly publications, are not an effective way of assessing impact of digital content. These issues are problematic in the field of Digital Humanities where there is a need to effectively assess impact to justify its continued funding and existence. A number of qualitative and quantitative methods exist that can be used to monitor the use of digital resources in various contexts although they have yet to be applied widely. These have been made available to the creators, managers, and funders of digital content in an accessible form through the TIDSR (Toolkit for the Impact of Digital Scholarly Resources) developed by the Oxford Internet Institute. In 2011, the authors of this article developed the SPHERE project (Stormont Parliamentary Hansards: Embedded in Research and Education) specifically to use TIDSR to evaluate the use and impact of The Stormont Papers , a digital collection of the Hansards of the Stormont Northern Irish Parliament from 1921 to 1972. This article presents the methodology, findings, and analysis of the project. The authors argue that TIDSR is a useful and, critically, transferrable method to understand and increase the impact of digital resources. The findings of the project are modified into a series of wider recommendations on protecting the investment in digital resources by increasing their use, value, and impact. It is reasonable to suggest that effectively showing the impact of Digital Humanities is critical to its survival.

The Data Documentation Initiative (DDI) specification has gone through significant development in recent years. Most Health and Demographic Surveillance System (HDSS) researchers in Low and Middle Income Countries (LMIC) are, however, unclear on how to apply it to their work. This paper sets out considerations that LMIC HDSS researchers need to make regarding DDI use. We use the Kisesa HDSS in Mwanza Tanzania as a prototype. First, we mapped the Kisesa HDSS data production process to the Generic Longitudinal Business Process Model (GLBPM). Next, we used existing GLBPM to DDI mapping to guide us on the DDI elements to use. We then explored implementation of DDI using the tools Nesstar Publisher for the DDI Codebook version and Colectica Designer for the DDI Lifecycle version. We found the amounts of metadata entry comparable between Nesstar Publisher and Colectica Designer when documenting a study from scratch. The majority of metadata had to be entered manually. Automatically extracted metadata amounted to at most 48% in Nesstar Publisher and 33% in Colectica Designer. We found Colectica Designer to have stiffer staff training needs and software costs than Nesstar Publisher. Our study shows that, at least for HDSS in LMIC, it is unlikely to be the amount of metadata entry that determines the choice between DDI Codebook and DDI Lifecycle but rather staff training needs and software costs. LMIC HDSS studies would need to invest in extensive staff training to directly start with DDI Lifecycle or they could start with DDI Codebook and move to DDI Lifecycle later.

The probability of winning games of tennis has been modelled in terms of the probability of the server winning an individual point. These models are based on the assumptions of stationarity of the point and interdependence. Stationarity is the assumption that the outcome of tennis points is not influenced by the game score at the beginning of the point. The purpose of the current investigation was to compare the outcomes of tennis points during break points and non-break points using data from 528 men's singles tennis matches from all four Grand Slam tournaments in 2008 and 2009. The retrospective probability of the receiver winning a point was 0.42 ± 0.23 during break points which was significantly greater than the 0.38 ± 0.10 during non-break points (P < 0.001). This, in turn, led to players creating significantly more break points than expected (P < 0.001) and breaking serve more frequently than expected (P < 0.001) for the points won when receiving serve. This is evidence that stationarity ca...

This article provides a case study of work performed at King's College London to survey information management practices, policies, and procedures applied by data creators and managers within three research units and three business units, and to determine the risk factors that may limit access and use of their digital assets over time. The assessment framework adopted to assess practices brings together components of the Data Asset Framework to analyze ad hoc data handling processes performed within departments, and combines it with the system-level Digital Repository Audit Methodology Based on Risk Assessment evaluation framework to identify the potential risks that may occur and the consequences to the institution or individual unless action is taken. It was found that data management activities within the academic units are comparable to a curate's egg, containing many actions performed in conformance to best practice, but also including poorly considered approaches that have the potential to restrict ...

It is well recognised that the period of time in which digital research may remain accessible is likely to be short in comparison to the period in which it will continue to hold intellectual value. Although many digital preservation strategies are effective for simple resources, it is not always possible to confirm that all of the significant properties - the characteristics that contribute to the intended meaning - have been maintained when stored in different formats and software environments. The paper outlines methodologies being developed by InterPARES, PLANETS and other projects in the international research community to support the decision-making process and highlights the work of four recent JISC-funded studies to specify the significant properties of vector images, moving images, software and learning objects.

This paper describes the FISHNet project, which developed a repository environment for the curation and sharing of data relating to freshwater science, a discipline whose research community is distributed thinly across a variety of institutions, and usually works in relative isolation as individual researchers or within small groups. As in other “small sciences”, these datasets tend to be small and “hand-crafted”, created to address particular research questions rather than with a view to reuse, so they are rarely curated effectively, and the potential for sharing and reusing them is limited. The paper addresses a variety of issues and concerns raised by freshwater researchers as regards data sharing, describes our approach to developing a repository environment that addresses these concerns, and identifies the potential impact within the research community of the system.