Participating in an archaeological field school is one of the only educational experiences that nearly all professional archaeologists have during their training. As a result, field schools are uniquely suited to provide experiential education in emerging skills that all archaeologists will need, such as information and data literacies at all stages of the contemporary research and publishing cycle. The “embedded” librarian program in the University of New Brunswick's Downeast Maine Coastal Archaeology Field School is an effective means to deploy that focused expertise to help students better understand the relationship between fieldwork, data, and dissemination. At the same time, being in the field provides librarians with the knowledge to respond more effectively to the complex data management and research needs of archaeologists. We encourage large research projects to consider librarians as specialist members of the research team.

The availability of digital data in the fourth industrial revolution brings different trends with new opportunities and challenges for the engineering design community. As an opportunity, these trends would impact engineering design. However, the challenge is finding applications for these trends in engineering design. Crowdsourcing is one of the trends inspired by digital data. It is outsourcing an individually performed task to be mass-performed. This paper explores the application of crowdsourcing in identifying engineering design problems. Identifying an engineering design problem is an aspect of engineering design considered challenging but necessary for inventions. Secondary data from 63 invention-related cases and an interview with a renowned UK inventor are presented. The data contains scenarios on how the engineering design problems solved to qualify for a UK patent grant or application are identified. Lessons from the case studies are presented and discussed, especially regarding crowdsourcing engineering design problems. These seem to be promising ways of supporting the identification of new engineering design problems with inventive benefits once solved.

This article focuses on the control of international mobility through the gathering, processing, and sharing of air travellers’ data. While a lot has been written about pre-emptive rationalities of security translated into the functionalities of IT systems used for border controls, we take a step further and investigate how these rationalities are operationalised through data transfer, screening, validation, discarding, profiling, contextualisation, calibration, and adjustment practices. These practices may seem banal and technical; however, we demonstrate how they matter politically as they underpin the making of international security. We do so by analysing the work of Passenger Information Units (PIUs) and retracing how they turn Passenger Name Record (PNR) data into actionable intelligence for counterterrorism and the fight against serious crime. To better understand the work of PIUs, we introduce and unpack the concept of ‘epistemic fusion’. This explicates how security intelligence comes into being through practices that pertain to cross-domain data frictions, the contextualisation of data-driven knowledge through its synthesis with more traditional forms of investigatory knowledge and expertise, and the adjustment of the intelligence produced to make it actionable on the ground.

Cet article fait état des pratiques marketing de quatre partis politiques (Coalition avenir Québec, Parti libéral du Québec, Parti québécois, Québec solidaire) en vue de l’élection générale québécoise de 2018. La couverture médiatique sur la pratique du marketing politique au Québec laissait présager une adoption plus marquée de l'approche marketing en 2018, notamment grâce à une utilisation soutenue des données numériques. Pour vérifier cette hypothèse, des entrevues semi-dirigées ont été menées auprès du personnel de campagne de ces formations. Nos résultats stipulent que la planification électorale se fait bel et bien dans un esprit de marketing politique. Les partis pratiquent toutefois un marketing partiel : ils mobilisent principalement l'intelligence de marché à des fins tactiques. Le numérique entraîne un raffinement de cette approche publicitaire. Finalement, l'application du concept de data-driven campaign n'est pas encore pleinement intégrée au Québec.

Collections care practices have become professionalized in the last 30 years, in large part because of the work of organizations such as the American Alliance of Museums, the Canadian Conservation Institute, the Society for the Preservation of Natural History Collections, the American Institute for Conservation, and others in the museum sphere. Advances in preservation and management have benefited the discipline of archaeology in the field and laboratory. This thematic issue provides an updated perspective on the current happenings in the repository, highlighting innovative techniques and practices that collections specialists employ when managing the archaeological record. This article considers a macroview of the issues surrounding archaeological curation today and ponders what the future of collections preservation can and should look like.

Managing collections means ensuring that the data about them are useful, available, and accurate. In addition to the technical aspects of data management, there are layers of political and social structure that direct the construction and use of collections data. The Minnesota Historical Society (MNHS) employs a set of data standards that allows us to gather electronic cataloging data from a wide community of archaeology researchers who are depositing collections at our institution. Though met with initial resistance, these standards have facilitated publication in Open Context as linked open data. Furthermore, institutional discussions concerning Creative Commons licensing and the cultural sensitivity of collections data were precipitated by publication, highlighting the role of social agreement in data management. We found that successful employment of data standards must take into account the needs of the various stakeholders and further their interests. Standards will be most useful and successful when they are lightweight, are supported by training and documentation, and exist as part of a system that allows for more than one way to characterize the collections.

Data are the foundation of modern observational science. High-quality science relies on high quality data. In Antarctica, unlike elsewhere, researchers must disperse data and conduct science differently. They must work within the laws enacted under Antarctic Treaty that defines Antarctica as a continent for peace and science, where data sharing and international collaboration are requisite keystones. Scientists also work under oversight guidance of the Scientific Committee on Antarctic Research (SCAR). In the last decade, rapid technological advances and vast increase in digital data volumes have changed the ways data are acquired, communicated, analysed, displayed and reported. Yet, the underlying science culture in which data are funded, utilised and cared for has changed little. Science-culture changes are needed for greater progress in Antarctic science.

We briefly summarise and discuss aspects of Antarctic ‘data care’, which is a subset of data management. We offer perceptions on how changes to some aspects of current science-culture could inspire greater data sharing and international collaboration, to achieve greater success. The changes would place greater emphasis on data visualisation, higher national priority on data care, implementation of a data-library concept for data sharing, greater individual responsibility for data care, and further integration of cultural arts into data and science presentations.

Much effort has gone into data management in the international community, and there are many excellent examples of successful collaborative Antarctic science programs within SCAR built on existing data sets. Yet, challenges in data care remain and specific suggestions we make deserve attention by the science community, to further promote peace and progress in Antarctic science.

Radix Sort is a sorting algorithm based on analyzing digital data. We study the number of swaps made by Radix Select (a one-sided version of Radix Sort) to find an element with a randomly selected rank. This kind of grand average provides a smoothing over all individual distributions for specific fixed-order statistics. We give an exact analysis for the grand mean and an asymptotic analysis for the grand variance, obtained by poissonization, the Mellin transform, and depoissonization. The digital data model considered is the Bernoulli(p). The distributions involved in the swaps experience a phase change between the biased cases (p ≠ ½) and the unbiased case (p = ½). In the biased cases, the grand distribution for the number of swaps (when suitably scaled) converges to that of a perpetuity built from a two-point distribution. The tool for this proof is contraction in the Wasserstein metric space, and identifying the limit as the fixed-point solution of a distributional equation. In the unbiased case the same scaling for the number of swaps gives a limiting constant in probability.