Search results

To rescue at-risk historical scientific data stored at the McGill Observatory, the objectives of the Data Rescue Archive Weather (DRAW) project are: to build a repository; to develop a protocol to preserve the data in weather registers; and to make the data available to research communities and the public. The paper aims to discuss these issues.

The DRAW project adopts an open archive information system compliant model as a conceptual framework for building a digital repository. The model consists of data collection, conversion, data capture, transcription, arrangement, description, data extraction, database design and repository setup.

A climate data repository, as the final product, is set up for digital images of registers and a database is designed for data storage. The repository provides dissemination of and access to the data for researchers, information professionals and the public.

Doing a quality check is the most important aspect of rescuing historical scientific data to ensure the accuracy, reliability and consistency of data.

The DRAW project shows how the use of historical scientific data has become a key element in research analysis on scientific fields, such as climatology and environmental protection.

The historical climate data set of the McGill Observatory is by nature unique and complex for preservation and research purposes. The management of historical scientific data is a challenge to rescue and describe as a result of its heterogeneous and non-standardized form.

It is a well held belief that the full moon period and the date Friday 13th has an impact on the number of emergency call outs for emergency services. The purpose of this paper is to critically explore that belief. It also examines the versatility and richness of response records, and demonstrates the effectiveness of combining data sets.

The work takes four varied data sets, from four rescue agencies along with the International Search and Rescue Database and compared the average number of calls on a full moon night, non-full moon and full moon period (the full moon night, the day before and day after). The average number of incidents on Friday 13th was also investigated. It uses a statistical approach to test the difference between “normal” dates and those dates traditionally believed to be busier.

Although there were differences between Friday 13th, full moon nights, full moon periods and “normal” days, the differences were in general extremely small, not significantly significant and in most cases actually dropped during the supposedly unlucky period. The exception to this is a very small increase in the average number of responses during full moons for most data sets, although this was not statistically significant. This paper concludes that there is no evidence in the data for any impact of the full moon upon rescue teams’ activities.

This research deals with a small set of responses, from the UK only, and addresses an issue that is clearly not the most pressing. However, it does demonstrate evidenced-based management in practice, in that resources have incorrectly been assigned in the past to these dates.

This work shows that preconceptions exist within the emergency services and that, without evidence-led management, resources can be allocated on hearsay. This shows that widely available software and techniques can be applied to organisational data and used to make management decisions more appropriate.

Rescue organisations are almost exclusively charity or public sector organisations, meaning that their budgets are sourced from donations or the tax-payer. Putting to bed misconceptions over resources for certain dates will ultimately benefit society in those terms.

There has been very little work on this phenomenon, although some works on A&E department admissions have taken place. This is the only work to date to combine data in this way for this purpose.

This case presents some of the entrepreneurial challenges faced by a female leader in the technology sector who conceived a new product based on her passion to help others especially those most disadvantaged.

Upon completion of this case study, students should be able to prepare supply chain and distribution analysis that considers ethics and sustainability, integrate philanthropic efforts as part of an organizational strategy and recognize strategies to promote equity within and beyond an organization.

Connie Stacey (she/her) is an entrepreneur and president of Growing Greener Innovations, an award-winning battery energy storage company based in Alberta, Canada, with a mission to end energy poverty globally. With the emergence of COVID-19 as a global pandemic in 2020, Stacey turned her attention to an innovation called Project Rescue, a ventilator that uses non-identifying patient vitals to track data. It serves as a pandemic early warning system, addressing two key challenges: pandemic data are prone to error, and real-time information is non-existent after the pandemic has spread. This new product was conceived based on her passion to help others, especially those most disadvantaged. This multi-faceted case focuses on the many challenges that Stacey and her team needed to address. The dilemma in this case centres on establishing supply chains amid a pandemic, as well as prioritizing the corporate social responsibility elements of philanthropy and equity within her organization (and beyond).

This case is appropriate for third- or fourth-year undergraduate or graduate-level students.

In addition to “call out boxes” throughout the case and teaching note, additional readings/links/videos are outlined below. (These supplementary materials, “Teaching Tips”, are included in the teaching notes as well.)

CCS 11: Strategy.

Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors.

This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation methods using distance- and volume-based aggregation error metrics. This paper additionally applies weighted versions of these metrics to account for the reality that demand events are nonhomogeneous. These metrics are applied to a large, highly variable, spatiotemporal demand data set of SAR events in the Pacific Ocean. Comparisons using these metrics are conducted between six quadrat aggregations of varying scales and two zonal distribution models using hierarchical clustering.

As quadrat fidelity increases the distance-based aggregation error decreases, while the two deliberate zonal approaches further reduce this error while using fewer zones. However, the higher fidelity aggregations detrimentally affect volume error. Additionally, by splitting the SAR data set into training and test sets this paper shows the stochastic zonal distribution aggregation method is effective at simulating actual future demands.

This study indicates no singular best aggregation method exists, by quantifying trade-offs in aggregation-induced errors practitioners can utilize the method that minimizes errors most relevant to their study. Study also quantifies the ability of a stochastic zonal distribution method to effectively simulate future demand data.

Data sharing is widely thought to help research quality and efficiency. Data sharing mandates are increasingly being adopted by journals and the purpose of this paper is to assess whether they work.

This study examines two evolutionary biology journals, Evolution and Heredity, that have data sharing mandates and make extensive use of Dryad. It uses a quantitative analysis of presence in Dryad, downloads and citations.

Within both journals, data sharing seems to be complete, showing that the mandates work on a technical level. Low correlations (0.15-0.18) between data downloads and article citation counts for articles published in 2012 within these journals indicate a weak relationship between data sharing and research impact. An average of 40-55 data downloads per article after a few years suggests that some use is found for shared life sciences data.

The value of shared data uses is unclear.

Data sharing mandates should be encouraged as an effective strategy.

This is the first analysis of the effectiveness of data sharing mandates.

A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture how library research data services (RDS) have developed and to assess the impact of this on the nature of academic libraries.

Questionnaire responses from libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, the UK and USA from 2018 are compared to a previous data set from 2014.

The evidence supports a picture of the spread of RDS, especially advisory ones. However, future ambitions do not seem to have seen much evolution. There is limited evidence of organisational change and skills shortages remain. Most service development can be explained as the extension of traditional library services to research data. Yet there remains the potential for transformational impacts, when combined with the demands implied by other new services such as around text and data mining, bibliometrics and artificial intelligence. A revised maturity model is presented that summarises typical stages of development of services, structures and skills.

The research models show how RDS are developing. It also reflects on the extent to which RDM represents a transformation of the role of academic libraries.

Practitioners working in the RDM arena can benchmark their current practices and future plans against wider patterns.

The study offers a clear picture of the evolution of research data services internationally and proposes a maturity model to capture typical stages of development. It contributes to the wider discussion of how the nature of academic libraries are changing.

Smart city developments have been subjected to technocratic envisioning and neoliberal urban developments. However, there have been attempts to reclaim the right to the city through organizing civic initiatives to widen the access to the making of future technologies and cities. This chapter draws on Mouffe’s concept of agonistic relations to explore the diversifying ideals, rhetoric, and practices of hackathon organization to consider how they might cooperate with or contest one another and provide alternative means to technology and city making. The chapter analyzes different ways of organizing hackathons and discusses the opportunities for participants with diverse social backgrounds, knowledges and technical competences to join and work together. By examining the conflictual positions, articulations, and arrangements to widen participation, the chapter suggests that more open, inclusive, and collaborative city-making events might be possible. Further work is needed to examine conflictual hackathon participation practices and other civic initiatives to pursue a more egalitarian smart city.

To serve their clients in a time of post-truth discourse and fake news, librarians need to understand the post-truth phenomenon. The purpose of this paper is to examine it, what is being done in response to it, and specifically what libraries can do.

Recent literature on the post-truth phenomenon was examined. Traditional assumptions about the role of libraries in promoting democracy were questioned and an alternative view was put forward. Libraries’ responses to the post-truth phenomenon were examined and critically discussed.

Traditional assumptions about the role of libraries and information and democracy are outdated. The susceptibility of people to false beliefs and the persistence of these beliefs in spite of corrective information, is the product of many factors, including the evolving media ecosystem and psychosocial processes which are the subject of ongoing empirical research. It not primarily an information or knowledge deficit, hence there are no simple antidotes to fake news. Libraries need to rethink their responses.

The paper deals with very recent developments and relies heavily on informal online resources.

Relevant library activities are examined and suggestions are made for developing appropriate library responses.

At the time of writing this was the first attempt in the library management literature to engage in a systematic and thoughtful manner with the literature on the post-truth phenomenon.

This study proposes a description of the civil society diplomacy that emerged in the early solutions found to fight the COVID-19 crisis. The author analyses this concept as the intersection of the social movements of individuals and civil society organisations' and international health care. Its purpose is to determine the international structure of the connective actors aimed to find concrete solutions against COVID-19 and to characterize the communication visible on Twitter towards this civil society engagement.

Based on a data-driven approach, the author collected a large dataset of tweets from Switzerland between March and June 2020 and conducted a computational text analysis methodology.

The results showed who the participants were, provided a visualisation of the digital networking process between engaged and mentioned participants at national and international levels, and determined the emotions that emerged during three event phases.

The study reveals that features of connective social care actions and strategic collective communication can illustrate civil society diplomacy for a shared cause in times of health crisis.