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Value co‐creation as a research topic has been a critical proposition of interest to a wide range of disciplines. In recent years, the field of cultural heritage has also developed a range of information practices to promote different forms of value co‐creation. While the body of literature has begun to accumulate, we still lack a comprehensive understanding of conceptual foundations and how value co‐creation is implemented in cultural heritage information practices. This paper conducted a hermeneutic literature review to understand and conceptualize the core aspects of value co‐creation in various cultural heritage information works. In particular, this paper provides a research mapping of the genres of co‐creation in cultural heritage information practices, the actors, and the roles played by the stakeholders. Further, this review provides an overview of the dominant value co‐creation models in the cultural heritage field. It distills the drivers of value co‐creation and the core value consequences that arise from a process perspective. Finally, this paper puts forward a thematic, theoretical, and methodological agenda for future work based on these findings. The review contributes to the literature by proposing an integrated conceptual framework that summarizes the core elements of value co‐creation in cultural heritage information practices. The framework also serves as a call for action, providing a general understanding of the conceptual foundation for future research. [ABSTRACT FROM AUTHOR]

When writing a research paper, the author has to select information to include in the paper to support various arguments. The information has to be organized and synthesized into a coherent whole through relationships and information structures. There is hardly any research on the information structure of research papers, and how information structure supports rhetorical and argument structures. Thus, this study is focused on information organization in the Abstract and Introduction sections of sociology research papers, analyzing the information structure of research objective, question, hypothesis, and result statements. The study is limited to research papers reporting research that investigated cause–effect relations between two concepts. Two semantic frames were developed to specify the types of information associated with cause–effect and comparison relations, and used as coding schemes to annotate the text for different information types. Six link patterns between the two frames were identified—showing how comparisons are used to support the claim that the cause‐effect relation is valid. This study demonstrated how semantic frames can be incorporated in discourse analysis to identify deep structures underlying the argument structure. The results carry implications for the knowledge representation of academic research in knowledge graphs, for semantic relation extraction, and teaching of academic writing. [ABSTRACT FROM AUTHOR]

This article explores the factors influencing the future citations of conference papers. We concentrated on the explanatory power of early attention on conference papers for citations collected from Google Scholar and Scopus. The early attention data includes users' online activities in a conference support system: CN3. Bookmarks from the bibliographic management system, Citeulike, were used as a collateral source of early attention. To examine the chronological contributions of 13 factors on citations, a multiple sequential regression analysis was conducted for three timepoints of the publication cycle—paper submission, time of conferences, and months after conferences. Our results illustrate that online readers' early attention of Citeulike bookmarks were found to have the most influence on the future impact of the conference papers. The early attention records from CN3 made noteworthy improvements to explaining both the Google and Scopus citations as well. We also found that the type of papers the number of papers presented at a conference, and the best article award records were significant factors influencing future citations. However, the magnitude of the effects made by online readers' early attention from both sources appears to be larger than these three traditional factors. [ABSTRACT FROM AUTHOR]

This paper explores the use of Fisher and Tronto's four phases of ethics of care (caring about, taking care of, caregiving, and care receiving) to three personal information management (PIM) frameworks, with a focus on PIM maintaining. The author argues that ethics of care can provide a theoretical foundation for PIM by using the four phases of caring to develop a perspective of PIM as a caring process using the categories of PIM as self‐care and PIM as caring for others. The paper begins by reviewing Fisher and Tronto's ethics of care, cites research in related fields that have applied ethics of care, and then describes how ethics of care could be applied to PIM research. To conclude, the author offers suggestions for how ethics of care can be applied to future PIM research in the following areas: better understand the motivations for PIM; the ways in which PIM can contribute to the social concepts of equality, justice, and trust and how social institutions can facilitate "good" PIM. [ABSTRACT FROM AUTHOR]

Non‐inferiority trials compare new experimental therapies to standard ones (active control). In these experiments, historical information on the control treatment is often available. This makes Bayesian methodology appealing since it allows a natural way to exploit information from past studies. In the present paper, we suggest the use of previous data for constructing the prior distribution of the control effect parameter. Specifically, we consider a dynamic power prior that possibly allows to discount the level of borrowing in the presence of heterogeneity between past and current control data. The discount parameter of the prior is based on the Hellinger distance between the posterior distributions of the control parameter based, respectively, on historical and current data. We develop the methodology for comparing normal means and we handle the unknown variance assumption using MCMC. We also provide a simulation study to analyze the proposed test in terms of frequentist size and power, as it is usually requested by regulatory agencies. Finally, we investigate comparisons with some existing methods and we illustrate an application to a real case study. [ABSTRACT FROM AUTHOR]

Keeping up with rapidly growing research fields, especially when there are multiple interdisciplinary sources, requires substantial effort for researchers, program managers, or venture capital investors. Current theories and tools are directed at finding a paper or website, not gaining an understanding of the key papers, authors, controversies, and hypotheses. This report presents an effort to integrate statistics, text analytics, and visualization in a multiple coordinated window environment that supports exploration. Our prototype system, Action Science Explorer ( ASE), provides an environment for demonstrating principles of coordination and conducting iterative usability tests of them with interested and knowledgeable users. We developed an understanding of the value of reference management, statistics, citation text extraction, natural language summarization for single and multiple documents, filters to interactively select key papers, and network visualization to see citation patterns and identify clusters. A three-phase usability study guided our revisions to ASE and led us to improve the testing methods. [ABSTRACT FROM AUTHOR]

The Garfield (Impact) Factor (GF) is one of the most frequently used scientometric indicators. In the present article it is shown that the main factors determining the value, of the mean of representing a set of journals are the number of articles published recently (articles referencing) Sated to those published in a previous time period (articles to be referenced) and the mean number of references in journal papers referring to the time period selected. It has been proved further that OF corresponds to the mean chance for citedness of journal papers. A new indicator, specific Impact Contribution (SIC), is Introduced, which characterizes the contribution of a subset of articles or a journal to the total impact of the respective articles or journals. The SIC index relates the share of a journal in citations divided by that in publications within a set of papers or journals appropriately selected. It is shown, however, that the normalized GFs of journals and the normalized SIC indicators are identical measures within any set of journals Selected. It may be stated therefore that Garfield Factors of journals (calculated correctly) are appropriate scientometric measures for characterizing the relative International eminence of journals within a set of journals appropriately selected. ft Is demonstrated further that SIC indicators (and so GF Indexes) correspond to the (number of citations per paper) indicators generally used, within the same set of papers. [ABSTRACT FROM AUTHOR]

Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about whether the salient words agree with those identified by humans as important. Objectives: The current study examines in‐line annotations from human annotators and saliency map annotations from a deep learning model (ELECTRA transformer) to understand how well both humans and machines provide evidence for their assigned label. Methods: Data were responses to test items across a mix of United States subjects, states, and grades. Humans were trained to annotate responses to justify a crisis alert label and two model interpretability methods (LIME, Integrated Gradients) were used to obtain engine annotations. Human inter‐annotator agreement and engine agreement with the human annotators were computed and compared. Results and Conclusions: Human annotators agreed with one another at similar rates to those observed in the literature on similar tasks. The annotations derived using the integrated gradients (IG) agreed with human annotators at higher rates than LIME on most metrics; however, both methods underperformed relative to the human annotators. Implications: Saliency map‐based engine annotations show promise as a form of explanation, but do not reach human annotation agreement levels. Future work should examine the appropriate unit for annotation (e.g., word, sentence), other gradient based methods, and approaches for mapping the continuous saliency values to Boolean annotations. Lay Description: What is known about subject matter: Explainability of deep learning models is complicated by their large size, design, and complexity.Explainability methods in deep learning exist but have not been rigorously tested.Saliency maps, as a form of explainability, can be used to generate engine annotations.Human annotations can serve as basis for comparison. What paper adds to knowledge: How well human annotations work in one domain (crisis paper identification).How well two engine annotation methods match human annotations. Implications of study findings: Human annotations have reasonable reliability.Engine annotations have lower reliability than humans.Model‐based engine annotations perform better than model‐agnostic engine annotations. [ABSTRACT FROM AUTHOR]

This paper focuses on data science in digital cultural heritage in Brazil, where there is a lack of systematized information and curated databases for the integrated organization of documentary knowledge. Thus, the aim was to systematically map the different forms of information organization and representation applied to objects from collections belonging to institutions affiliated with the federal government's Special Department of Culture. This diagnosis is then used to discuss the requirements of devising strategies that favor a better data science information infrastructure to reuse information on Brazil's cultural heritage. Content analysis was used to identify analytical categories and obtain a broader understanding of the documentary sources of these institutions in order to extract, analyze, and interpret the data involved. A total of 215 hyperlinks that can be considered cultural collections of the institutions studied were identified, representing 2,537,921 cultural heritage items. The results show that the online publication of Brazil's digital cultural heritage is limited in terms of technology, copyright licensing, and established information organization practices. This paper provides a conceptual and analytical view to discuss the requirements for formulating strategies aimed at building a data science information infrastructure of Brazilian digital cultural collections that serves as future projects. [ABSTRACT FROM AUTHOR]

GLAM organizations have been digitizing their collections and making them available for the public for several decades. Recent methods for publishing digital collections such as "GLAM Labs" and "Collections as Data" provide guidelines for the application of computational methods to reuse the contents of cultural heritage institutions in innovative and creative ways. Jupyter Notebooks have become a powerful tool to foster use of these collections by digital humanities researchers. Based on previous approaches for quality assessment, which have been adapted for cultural heritage collections, this paper proposes a methodology for assessing the quality of projects based on Jupyter Notebooks published by relevant GLAM institutions. A list of projects based on Jupyter Notebooks using cultural heritage data has been evaluated. Common features and best practices have been identified. A detailed analysis, that can be useful for organizations interested in creating their own Jupyter Notebooks projects, has been provided. Open issues requiring further work and additional avenues for exploration are outlined. [ABSTRACT FROM AUTHOR]

Information and communication technology for development (ICT4D) is a field of research concerned with studying how information and communication technologies (ICTs) can be used to improve the socio‐economic situation of marginalized communities in developing countries. The authors identify the preservation of the information provided or accessed during ICT4D projects as a critical gap in ICT4D research. They argue that archival science, an information discipline concerned with the preservation of recorded information, provides theories and models that can help make ICT4D projects more sustainable. They discuss the creation of analog backups by participants in an ICT4D project in Bangladesh as an example of communities taking the initiative to remedy the limitations of an ICT4D project with simple pen and paper technology to preserve the information they wanted to keep. Conversely, they argue that insights on how marginalized communities interact with and preserve information gained through ICT4D projects can enrich archival science and foster the development of more inclusive theories and practices. Finally, they suggest areas for interdisciplinary research between ICT4D and archival science. [ABSTRACT FROM AUTHOR]

It is clear that the African region faces a number of serious oral diseases, either because of their high prevalence or because of the severe tissue damage or death that can occur. Previous approaches to oral health in Africa have failed to recognise the epidemiological priorities of the region or to identify reliable and appropriate strategies to assess them. Efforts have consisted of an unplanned, ad hoc and spasmodic evolution of curative oral health services. This document focuses on the most severe oral problems that people have to live with like noma, oral cancer and the oral consequences of HIV/AIDS infection. It proposes a strategy for assisting member states and partners to identify priorities and interventions at various levels of the health system, particularly at the district level. The strategy aims at strengthening the capacity of countries to improve community oral health by effectively using proven interventions to address specific oral health needs. The strategy identifies five main ‘programmatic areas’, including (i) the development of national oral health strategies and implementation plans, (ii) integration of oral health in other programmes, (iii) delivery of effective and safe oral health services, (iv) regional approach to education and training for oral health, and (v) development of effective oral health management information systems. Many of the programmatic areas share similar characteristics described as a ‘strategic orientation’. These strategic orientations give effect to the concepts of advocacy, equity, quality, partnership, operational research, communication and capacity building. The WHO Regional Committee for Africa (RC) is invited to review the proposed oral health strategy for the African region for the period 1999–2008 and provide an orientation for the improvement of oral health in member states in the region. [ABSTRACT FROM AUTHOR]

This paper describes ePaper, a research prototype system of a personalized newspaper on a mobile reading device. The ePaper aggregates content (i.e., news items) from various news providers, classifies the news items according to concepts from a news domain ontology, and delivers an electronic newspaper to each subscribed user (reader). The system personalizes the content of the newspaper according to the user's profiles and preferences by applying ontological content-based and collaborative filtering algorithms. The user's profile is updated implicitly and dynamically, based on the tracking of their reading. Beyond personalization, the ePaper can also provide the user with a “standard edition” of a selected newspaper, as well as browsing capabilities in a repository of news items. The layout of the newspaper is adapted to the specifications of the reading device and to the user's preferences. In this overview paper, we highlight the main research challenges involved in the development of ePaper and describe how we addressed them. [ABSTRACT FROM AUTHOR]

A second presidential social media transition in the United States occurred as Joe Biden took office on January 20, 2021. In the years since Barack Obama pioneered the use of platforms like Facebook and Twitter while President, Donald Trump shaped his Presidency around the use of Twitter, primarily through a personal account created before entering politics. In this paper, we examine Donald Trump's use of Twitter during his presidency as a lens through which to understand the ongoing archival preservation and data management challenges posed by social media platforms. The blurred lines between public and private records, deleting tweets, and the preservation issues that appeared after his suspension from Twitter and other platforms following the January 6, 2021 insurrection at the US Capitol all highlight an urgent, ongoing need by archivists, digital preservationists, and information scholars to consider how we might collect and manage social media records in an ever‐changing information landscape. This paper draws primarily on publicly available information from existing preservation initiatives to analyze the state of digital preservation for presidential records. Our findings highlight how both public and private entities manage and provide access to Donald Trump's tweets, pointing to broader implications for social media data preservation. [ABSTRACT FROM AUTHOR]

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT‐based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top‐K main paths extracted from various time slices of semantic citation network. In addition, a three‐way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics‐agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas. [ABSTRACT FROM AUTHOR]

This paper proposes a theory of life transitions focused on information behavior. Through a process of meta‐ethnography, the paper transforms a series of influential theories and models into a theory of transitions for use in Information Science. This paper characterizes the psychological processes involved in transitions as consisting of three main stages, Understanding, Negotiating, and Resolving, each of which have qualitatively different information behaviors and which require different types of information support. The paper discusses the theoretical implications of this theory and proposes ways in which the theory can be used to provide practical support for those undergoing transitions. [ABSTRACT FROM AUTHOR]

Information Technology (IT) investments in the public sector are large, and it is essential that they lead to benefits for the organisations themselves and wider society. While there is evidence suggesting a positive connection between the existence of benefits management practices and the realisation of benefits, less is known about how to implement such practices effectively. The aim of this paper is to provide insights into when benefits are most likely to be realised, and how benefits management practices and roles should be implemented, in order to have a positive effect on the success of projects in terms of realising benefits. We collected data relating to 10 public IT projects in Norway. For each project, information on benefits management was collected from project documents by interviewing the project owners and benefits owners and via follow‐up surveys. The benefits with the highest degree of realisation were those internal to the organisation, while those with the lowest degree were societal benefits. Projects assessed as having more specific, measurable, accountable, and realistically planned benefits were more successful in terms of realising benefits. Benefit owners were most effective when they were able to attract attention to the benefits to be realised, had a strong mandate, and had the domain expertise. [ABSTRACT FROM AUTHOR]

Zoos and aquaria, often regarded as preservation‐cum‐entertainment enterprises, are also actors in the effort to curb the biodiversity crisis: raising awareness, supporting conservation, and conducting research. We assessed trends in zoo and aquaria research topics and study organisms over time worldwide. For the zoos and aquaria registered in the Species360's Zoological Information Management System and the World Association of Zoos and Aquariums, we compiled metadata on their research published in the peer‐reviewed literature indexed in Scopus and carried out a keyword frequency analysis. The production of scientific papers by zoos increased at a much faster rate than the average accrual of scientific papers in the literature. Evolution of research themes ran parallel to that of biological sciences (e.g., development of molecular genetics or increased awareness about conservation). The focus of 48.5% of zoo‐led research was on vertebrates, of which mammal research was 33.7%. Whether zoos are effectively contributing to conservation may still be debatable, but our results highlight their institutional efforts to increase knowledge about the species in their care. Article impact statement: Research led by zoos has exploded over the last decade, particularly research on conservation and genetics. [ABSTRACT FROM AUTHOR]

Responding to disasters triggered by natural hazards is a deeply political process, but it is usually presented by practitioners as an apolitical endeavour. This is striking when disasters occur in authoritarian and politically highly polarised conflict‐affected settings. Although the literature provides leads as to why and how humanitarians depoliticise aid, there has been little empirical research on the implications of depoliticisation, especially at the community level. Based on qualitative fieldwork that focused on the drought responses that overlapped with the 2016–19 sociopolitical crises in Zimbabwe, this paper details the practices, motivations, and implications of humanitarian depoliticisation. It differentiates between strategic, coerced, and routine managerial depoliticisation, and argues that, in an authoritarian conflict‐affected setting, depoliticisation strategically allows state and non‐state actors to defuse sensitive issues and actor relations and to remain safe. However, depoliticisation can also have implications for information management, monitoring, accountability, and protection, and thus ultimately for upholding humanitarian principles. [ABSTRACT FROM AUTHOR]

The digital management of engineering construction is one of the primary tasks of smart construction sites. In the current practice of construction site information management, there are a series of fraudulent behaviors such as engineering data being forged and modified and this seriously interferes with the safety supervision of engineering projects. In order to improve the security and traceability of multi‐type engineering data, this paper presents a framework of system for construction site information management using blockchain and smart contracts. In this method, multiple independent smart contracts are developed for different data types. It ensures that the system can dynamically deploy new smart contracts without interrupting service, facilitating the expansion of scenario services. More importantly, the data analysis function is extended to the terminal, which allows the integration of different data analysis algorithms such as deep learning into information management. The design breaks the restriction that only rule‐based data analysis can be performed. Meanwhile, the distributed federation architecture ensures that the data cannot be tampered with. Finally, the three most common types of data (namely text, time‐series, and image) were used to verify the security and stability of the management system. [ABSTRACT FROM AUTHOR]

Privacy‐enhancing technologies that incorporate a socially meaningful conception of privacy, one that meets people's expectations and is ethically defensible, need to factor in contextual privacy norms and information governance as part of their design. This involves understanding what information handling practices users deem acceptable, what factors influence users' perceptions and behaviors, and how informational norms evolve. In this paper, we present GKC‐CI, a unifying framework for examining contextual privacy norms and information governance in a given context to help structure research inquiries around these questions. [ABSTRACT FROM AUTHOR]

Background: Fungal skin infections are recognised as one of the most common health disorders globally, and dermatophyte infections of the skin, hair and nails are the most common fungal infections. Dermatophytes can be classified as anthropophilic, zoophilic or geophilic species based on their primary habitat association, and this classification makes epidemiological analysis useful for the prevention and control of these infections. The Irish contribution to the epidemiology of these infections has been scant, with just two papers (both reporting paediatric tinea capitis only) published in the last 20 years, and none in the last seven. Objectives: To perform a comprehensive retrospective epidemiological analysis of all dermatological mycology tests performed in University Hospital Limerick over a 20‐year period. Methods: All mycology laboratory test results were extracted from the Laboratory Information Management System (LIMS, iLab, DXC Technologies) from 2001 to 2020 inclusive for analysis. Specimen types were categorised according to the site of sampling. The data were analysed using Microsoft Excel. Results: About 12,951 specimens of skin, hair and nails were studied. Median patient age was 42 years (IQR 26–57) with a slight female preponderance (57.2%). Two thirds of samples (67%, n = 8633) were nail, 32% were skin scrapings (n = 4118) and 200 hair samples (1.5%) were received. Zoophilic dermatophytes were more commonly present in females (38% F, 23% M, proportion of dermatophytes) and in those under 10 years of age or from 45 to 70 years (36% and 34% zoophiles, respectively, proportion of dermatophytes), although anthropophiles predominated every age and gender category. Anthropophiles had their highest prevalence in the 10–20 years age category (80% anthropophiles, proportion of dermatophytes), and yeast infections were more prevalent in older patients (29% of >60 year olds vs. 17% of <60 year olds, proportion of all fungal positives). Trichophyton rubrum was the most prevalent pathogen detected, accounting for 53% of all dermatophytes detected, 61% of those detected from nail samples and 34% from skin and hair samples. Trichophyton tonsurans was the most prevalent dermatophyte in tinea capitis, accounting for 37% of dermatophytes detected. Both of these organisms are anthropophilic, and this group showed consistently increased prevalence in proportion to all fungal isolates. The proportion of this dermatophyte class (anthropophiles) increased among both nail samples and skin/hair samples during the study period, from 55% of samples in the first 5 years of the study (2001–2005) to 88% (proportion of dermatophytes) in the final 5 years. Conversely, yeast detection decreased. Conclusions: This study provides a detailed overview of the epidemiology of the fungal cultures of skin, nail and hair samples in the Mid‐West of Ireland over a 20‐year period. Monitoring this changing landscape is important in identifying likely sources of infections, to identifying potential outbreaks, and may help guide empiric treatment. To the best of our knowledge, this study provides the first detailed analysis from Ireland of fungal detections from skin, hair and nail samples, and is the first epidemiological fungal report of any kind in over 7 years. [ABSTRACT FROM AUTHOR]

The article reviews the book “Paper Machines: About Cards & Catalogs, 1548–1929,” by Markus Krajewski.

In this opinion paper, we frame a discussion on paradigm shift(s) in the field of information. We believe that in this astonishing historical moment of new directions and new opportunities both the existing paradigms and conceptual models in the field of information can benefit from re‐examination to stay current with the times. We propose a framework articulating key narratives associated with the why, what, how, and who dimensions to discuss paradigm shift(s). The purpose of this opinion paper is to initiate dialogues on ground‐breaking ideas and innovative solutions as well as support research that addresses contemporary challenges in the field of information. [ABSTRACT FROM AUTHOR]

The documentation of the tunneling process is a crucial task of every tunnel construction project. It provides evidence of the work performed and thus, serves as a basis for invoicing and for several further analyses. Therefore, continuous digitalisation of this documentation is essential. For this purpose, we provide a digital Tunneling Information Management System (TIMS), which is a prototypically implemented software tool for replacing the still common paper‐based documentation process of tunneling projects using the New Austrian Tunneling Method (NATM). The data model presented here defines the data structures managed by this tool. Based on this, the software architecture and the implementation of TIMS is shown. [ABSTRACT FROM AUTHOR]

Summary: With the development of cloud computing, the security of information has gradually become the focus of people. The patient information processed by the medical system has a very high sensitivity and privacy. If there is a leak, it will have a great impact on the patients. The purpose of this study is to explore the privacy information antistealing control method of medical system based on cloud computing. In this paper, through big data analysis, experimental research, variable comparison, and other methods, combined with modern security management means, we carry out the algorithm experiment and research on the privacy information antistealing control means. The result is that the running time of the three algorithms is 18, 16, and 10 s in turn when the algorithm runs 1000 times. It can be seen that the operation time of the enhanced encryption algorithm in this study is less than the initial algorithm by 8 s, the speed is increased by more than 40%. The conclusion is to improve the efficiency of data computing time and make the encryption process more efficient and accurate. The privacy data protection of medical system plays a good role. [ABSTRACT FROM AUTHOR]

Background: Information specialists conducting searches for systematic reviews need to consider key questions around which and how many sources to search. This is particularly important for public health topics where evidence may be found in diverse sources. Objectives: The objective of this review is to give an overview of recent studies on information retrieval guidance and methods that could be applied to public health evidence and used to guide future searches. Methods: A literature search was performed in core databases and supplemented by browsing health information journals and citation searching. Results were sifted and reviewed. Results: Seventy‐two papers were found and grouped into themes covering sources and search techniques. Public health topics were poorly covered in this literature. Discussion: Many researchers follow the recommendations to search multiple databases. The review topic influences decisions about sources. Additional sources covering grey literature eliminate bias but are time‐consuming and difficult to search systematically. Public health searching is complex, often requiring searches in multidisciplinary sources and using additional methods. Conclusions: Search planning is advisable to enable decisions about which and how many sources to search. This could improve with more work on modelling search scenarios, particularly in public health topics, to examine where publications were found and guide future research. [ABSTRACT FROM AUTHOR]

In many orphan diseases and pediatric indications, the randomized controlled trials may be infeasible because of their size, duration, and cost. Leveraging information on the control through a prior can potentially reduce sample size. However, unless an objective prior is used to impose complete ignorance for the parameter being estimated, it results in biased estimates and inflated type‐I error. Hence, it is essential to assess both the confirmatory and supplementary knowledge available during the construction of the prior to avoid "cherry‐picking" advantageous information. For this purpose, propensity score methods are employed to minimize selection bias by weighting supplemental control subjects according to their similarity in terms of pretreatment characteristics to the subjects in the current trial. The latter can be operationalized through a proposed measure of overlap in propensity‐score distributions. In this paper, we consider single experimental arm in the current trial and the control arm is completely borrowed from the supplemental data. The simulation experiments show that the proposed method reduces prior and data conflict and improves the precision of the of the average treatment effect. [ABSTRACT FROM AUTHOR]

This article considers the interdisciplinary opportunities and challenges of working with digital cultural heritage, such as digitized historical newspapers, and proposes an integrated digital hermeneutics workflow to combine purely disciplinary research approaches from computer science, humanities, and library work. Common interests and motivations of the above‐mentioned disciplines have resulted in interdisciplinary projects and collaborations such as the NewsEye project, which is working on novel solutions on how digital heritage data is (re)searched, accessed, used, and analyzed. We argue that collaborations of different disciplines can benefit from a good understanding of the workflows and traditions of each of the disciplines involved but must find integrated approaches to successfully exploit the full potential of digitized sources. The paper is furthermore providing an insight into digital tools, methods, and hermeneutics in action, showing that integrated interdisciplinary research needs to build something in between the disciplines while respecting and understanding each other's expertise and expectations. [ABSTRACT FROM AUTHOR]

Medicine is practiced in environments of volatility, uncertainty, complexity, ambiguity, and disruption (VUCAD). Medical educators are tasked with providing an education that prepares graduates to successfully practice medicine in those types of environments. While medical education is continually evolving to incorporate new content and educational approaches, there are two mega‐evolutions that have permeated medical education: increased curricular structure and content integration. Structure and integration are assumed to be positive changes; however, they may alter the development of higher cognitive skills such as information management, planning, breadth of approach, strategy, and initiative. As new graduates will practice in VUCAD environments, it seems prudent to consider the effects of medical education's mega‐evolutions on the development of higher cognitive skills critical to those types of environments. This paper explores the potential consequences of the increased curricular structure and content integration in medical education for learners who will practice in VUCAD environments and proposes a research agenda to better understand the relationship between curricular structure and integration and higher cognitive skill development. [ABSTRACT FROM AUTHOR]

The architectures of many neural networks rely heavily on the underlying grid associated with the variables, for instance, the lattice of pixels in an image. For general biomedical data without a grid structure, the multi‐layer perceptron (MLP) and deep belief network (DBN) are often used. However, in these networks, variables are treated homogeneously in the sense of network structure; and it is difficult to assess their individual importance. In this paper, we propose a novel neural network called Variable‐block tree Net (VtNet) whose architecture is determined by an underlying tree with each node corresponding to a subset of variables. The tree is learned from the data to best capture the causal relationships among the variables. VtNet contains a long short‐term memory (LSTM)‐like cell for every tree node. The input and forget gates of each cell control the information flow through the node, and they are used to define a significance score for the variables. To validate the defined significance score, VtNet is trained using smaller trees with variables of low scores removed. Hypothesis tests are conducted to show that variables of higher scores influence classification more strongly. Comparison is made with the variable importance score defined in Random Forest from the aspect of variable selection. Our experiments demonstrate that VtNet is highly competitive in classification accuracy and can often improve accuracy by removing variables with low significance scores. [ABSTRACT FROM AUTHOR]

The information professions need a paradigmatic shift to address the epistemicide happening within our field and the ways we have systematically undermined knowledge systems falling outside of Western traditions. Epistemicide is the killing, silencing, annihilation, or devaluing of a knowledge system. We argue epistemicide happens when epistemic injustices are persistent and systematic and collectively work as a structured and systemic oppression of particular ways of knowing. We present epistemicide as a conceptual approach for understanding and analyzing ways knowledge systems are silenced or devalued within Information Science. We extend Fricker's framework by: (a) identifying new types of epistemic injustices, and (b) by adding to Fricker's concepts of Primary and Secondary Harm and introducing the concept of a Third Harm happening at an intergenerational level. Addressing epistemicide is critical for information professionals because we task ourselves with handling knowledge from every field. Acknowledgement of and taking steps to interrupt epistemic injustices and these specific harms are supportive of the social justice movements already happening. This paper serves as an interruption of epistemic injustice by presenting actions toward justice in the form of operationalized interventions of epistemicide. [ABSTRACT FROM AUTHOR]

Erving Goffman's interest in spies and espionage is widely recognized in commentary on his work. Where did this interest come from? While the context of Cold War America provided the broad cultural horizon of this work, deeper roots may be found. Goffman's contact with two University of Chicago professors, Edward A. Shils and Douglas Waples, both of whom served in U.S. intelligence organizations during World War II, also shaped Goffman's interest in the subject. This paper explores these relationships and their connection to Goffman's writings on spies, secrecy, and information control in postwar America. Goffman's view of spies and espionage as analogues to American postwar lives is explored. [ABSTRACT FROM AUTHOR]

Background and objectives: Hospitals prepare for emergencies, but the impact on transfusion staff is rarely discussed. We describe the transfusion response to four major incidents (MIs) during a 6‐month period. Three events were due to terrorist attacks, and the fourth was the Grenfell Tower fire. The aim of this paper was to share the practical lessons identified. Methods: This was a retrospective review of four MIs in 2017 using patient administration systems, MI documentation and post‐incident debriefs. Blood issue, usage and adverse events during the four activation periods were identified using the Laboratory Information Management System (TelePath). Results: Thirty‐four patients were admitted (18 P1, 4 P2, 11 P3 and 1 dead). Forty‐five blood samples were received: 24 related to nine MI P1 patients. Four P1s received blood components, three with trauma and one with burns, and 35 components were issued. Total components used were six red blood cells (RBC), six fresh frozen plasma (FFP) and two cryoprecipitate pools. Early lessons identified included sample labelling errors (4/24). Errors resolved following the deployment of transfusion staff within the emergency department. Components were over‐ordered, leading to time‐expiry wastage of platelets. Careful staff management ensured continuity of transfusion services beyond the immediate response period. Debriefing sessions provided staff with support and enabled lessons to be shared. Conclusions: Transfusion teams were involved in repeated incidents. The demand for blood was minimal. Workload was related to sample handling rather than component issue. A shared situational awareness would improve stock management. A laboratory debriefing system offered valuable feedback for service improvement, staff training and support. [ABSTRACT FROM AUTHOR]

This paper is based on Victoria Charnock's MA dissertation carried out as part of her Masters in Leadership and Management in Healthcare at the University of Salford and supervised by Professor Hardiker. A review of current literature was conducted to provide a robust and dimensional definition of data quality in the field of health care. This was used as the basis on which to assess the effect that electronic health care records has had in practice, specifically on data quality and according to the dimensions of accuracy, completeness and use of data. All of the papers reviewed referred to the importance of accuracy and completeness, identifying the advantages of electronic health records in their use of standardized data entry controls. Drawing on the third dimension in the definition, use of data, the impact that system design may have on data quality and implications for staff training is further discussed and recommendations made. F.J. [ABSTRACT FROM AUTHOR]

A key challenge in crisis management is maintaining an adequate information position to support coherent decision‐making between a range of actors. Such distributed decision‐making is often supported by a common operational picture that not only conveys factual information but also attempts to codify a dynamic and vibrant crisis management process. In this paper, we explain why it is so difficult to move from information sharing towards support for distributed decision‐making. We argue that two key processes need to be considered: supporting both the translation of meaning and the transformation of interests between those on the front line and those in the remote response network. Our analysis compares the information‐sharing processes in three large‐scale emergency response operations in the Netherlands. Results indicate that on several occasions the collaborative decision‐making process was hampered because actors limited themselves to factual information exchange. The decision‐making process only succeeds when actors take steps to resolve their varying interpretations and interests. This insight offers important lessons for improving information management doctrines and for supporting distributed decision‐making processes. [ABSTRACT FROM AUTHOR]

Summary: Software‐defined networking (SDN) creates a platform to dynamically configure the networks for on‐demand services. SDN can easily control the data plane and the control plane by implementing the decoupling concept. SDN controller will regulate the traffic flow and creates the new flow label based on the packet dump received from the OpenFlow virtual switches. SDN governs both data information and control information toward the destination based on flow label, but it does not contain security measure to restrict the malicious traffic. The malicious denial‐of‐service (DoS) attack traffic is generated inside the SDN environment; it leads to the service unavailability. This paper is mainly focused on the detection of DoS attacks and also mitigates the malicious traffic by dynamically configuring the firewall. The SDN with dynamic access control list properties is emulated by mininet, and the experimental results exemplify the service unavailable gap between acceptance and rejection ratio of the packets. [ABSTRACT FROM AUTHOR]

The architectures of many neural networks rely heavily on the underlying grid associated with the variables, for instance, the lattice of pixels in an image. For general biomedical data without a grid structure, the multi-layer perceptron (MLP) and deep belief network (DBN) are often used. However, in these networks, variables are treated homogeneously in the sense of network structure; and it is difficult to assess their individual importance. In this paper, we propose a novel neural network called Variable-block tree Net (VtNet) whose architecture is determined by an underlying tree with each node corresponding to a subset of variables. The tree is learned from the data to best capture the causal relationships among the variables. VtNet contains a long short-term memory (LSTM)-like cell for every tree node. The input and forget gates of each cell control the information flow through the node, and they are used to define a significance score for the variables. To validate the defined significance score, VtNet is trained using smaller trees with variables of low scores removed. Hypothesis tests are conducted to show that variables of higher scores influence classification more strongly. Comparison is made with the variable importance score defined in Random Forest from the aspect of variable selection. Our experiments demonstrate that VtNet is highly competitive in classification accuracy and can often improve accuracy by removing variables with low significance scores. [ABSTRACT FROM AUTHOR]

Profile monitoring is referred to as monitoring the functional relationship between the response and explanatory variables. Traditionally, process control charts monitor the mean and/or the variance of a univariate quality characteristic. For several correlated quality characteristics, multivariate process control charts monitor the mean vector and/or the covariance matrix. However, monitoring the functional relationship between variables is sometimes more beneficial. One example is the power output of a Diesel engine and the amount of fuel injected should be related. In this paper, we propose a Kullback‐Leibler information (KLI) control chart for linear profiles monitoring in Phase II. The plotted statistics of the KLI chart are calculated based on a backward procedure. The functional relationship is described by linear regression. The performance of the proposed KLI control chart is compared with those of other existing control charts, especially the Generalized Likelihood Ratio (GLR) chart for both KLI and GLR charts do not require design parameters. The results show that (1) the KLI control chart is better than the GLR control chart in detecting the shift of variance in terms of Average Time to Signal, and (2) if the shift of the regression coefficient is small, the GLR chart outperforms the KLI chart, but if the size of shift is large, the KLI chart outperforms the GLR chart. The plotted statistics of KLI are compared to that of GLR. Their similarity is discussed. [ABSTRACT FROM AUTHOR]

Life expectancy is rising in most parts of the world as is the prevalence of chronic diseases. Suboptimal adherence to long‐term medications is still rather the norm than the exception, although it is well known that suboptimal adherence compromises the therapeutic effectiveness. Information and communications technology provides new concepts for improving adherence to medications. These so‐called telehealth concepts or services help to implement closed‐loop healthcare paradigms and to establish collaborative care networks involving all stakeholders relevant to optimising the overall medication therapy. Together with data from Electronic Health Records and Electronic Medical Records, these networks pave the way to data‐driven decision support systems. Recent advances in machine learning, predictive analytics, and artificial intelligence allow further steps towards fully autonomous telehealth systems. This might bring advances in the future: disburden healthcare professionals from repetitive tasks, enable them to timely react to critical situations, and offer a comprehensive overview of the patients' medication status. Advanced analytics can help to assess whether patients have taken their medications as prescribed, to improve adherence via automatic reminders. Ultimately, all relevant data sources need to be collated into a basis for data‐driven methods, with the goal to assist healthcare professionals in guiding patients to obtain the best possible health status, with a reasonable resource utilisation and a risk‐adjusted safety and privacy approach. This paper summarises the state‐of‐the‐art of telehealth and artificial intelligence applications in medication management. It focuses on 3 major aspects: latest technologies, current applications, and patient related issues. [ABSTRACT FROM AUTHOR]

We are witnessing a growing gap separating primary research data from derived data products presented as knowledge in publications. Although journals today more often require the underlying data products used to derive the results as a prerequisite for a publication, the important link to the primary data is lost. However, documenting the postprocessing steps of data linking, the primary data with derived data products has the potential to increase the accuracy and the reproducibility of scientific findings significantly. Here, we introduce the rBEFdata R package as companion to the collaborative data management platform BEFdata. The R package provides programmatic access to features of the platform. It allows to search for data and integrates the search with external thesauri to improve the data discovery. It allows to download and import data and metadata into R for analysis. A batched download is available as well which works along a paper proposal mechanism implemented by BEFdata. This feature of BEFdata allows to group primary data and metadata and streamlines discussions and collaborations revolving around a certain research idea. The upload functionality of the R package in combination with the paper proposal mechanism of the portal allows to attach derived data products and scripts directly from R, thus addressing major aspects of documenting data postprocessing. We present the core features of the rBEFdata R package along an ecological analysis example and further discuss the potential of postprocessing documentation for data, linking primary data with derived data products and knowledge. [ABSTRACT FROM AUTHOR]

Abstract: Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose a simple, continuous, and distributed controller for the second‐order multiagent system to achieve leader‐following trajectory tracking, by exploiting the control input information of neighbors (CIIN) and using proportional‐derivative (PD) control in terms of local neighborhood synchronization error. A constant time delay is introduced in the CIIN as a design parameter to avoid the algebraic loop issue arising from the control input coupling. We develop an easily testable condition on the PD gains to ensure that the resulting neutral‐type error system is input‐to‐state stable for an arbitrary bounded delay, and prove that when the leader's acceleration is a Lipschitz continuous function with respect to time, the ultimate bound of tracking errors is strictly increasing with respect to the introduced time delay. Moreover, we analyze the robustness of the controller with respect to model uncertainties and show its potential advantages over two existing controllers in balancing the steady‐state tracking precision, the communication cost, and the continuity of controller signal. Finally, extensive simulations are conducted to show the effect of the delay on system stability, to verify the condition on PD gains, to confirm the robustness of the controller, and to demonstrate the detailed advantages. [ABSTRACT FROM AUTHOR]

Background: Timely access to evidence increases the prospects for evidence informed decision making. We evaluated user experiences of a Clearing House for Health Policy with the aim of increasing access to evidence about the Uganda health system and interventions. Methods: We conducted in‐depth interviews with 15 potential users including policymakers, health policy advisors, health managers and researchers to provide evidence on their experience with the clearinghouse. On average participants took 20 minutes to first navigate the site and 45 minutes to perform search tasks and complete the interview. Results: Most respondents successfully searched for information with accuracy and completeness in a short time. Participants commended the performance and expressed high regard for the credibility of the clearinghouse. The majority felt that using the resource was worth their effort. The clearinghouse provided appropriate functionalities for information searching. Navigating and finding information from the site was achievable. However, inadequate background information about the site and lack of current information were widely reported. Conclusion: Our paper provides insights on the issues that can be addressed to improve online resources for health policy and system information in a limited resource setting. Users' experience of such resources can be improved by regularly appraising and appropriately indexing the contents, and optimising the capacity to customise information. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between external knowledge sourcing and a diverse set of innovation outcomes in rural and urban establishments in the U.S. Existing studies in the broader knowledge management literature principally examine firms in a single industry, overwhelmingly rely on patent data to proxy for innovation, and cannot account for the innovations of businesses in rural American markets. By addressing these limitations using data from the 2014 Rural Establishment Innovation Survey of the USDA's Economic Research Service, this research provides novel insights into how externally acquired knowledge by American establishments may support innovation. Results of the analysis suggest that external knowledge sourcing may specifically promote product, process, and green innovation in U.S. firms. While collective results when external sources of information are divided by industry orientation fail to show that sources outside of a firm's industry play a dominant role in the innovation processes of American establishments in general, findings provide evidence for an outsized impact of these relationships within rural establishments specifically and suggest that external knowledge sourcing from extra‐industry organizations is most critical for promoting successful innovation in rural firms. Results additionally indicate that knowledge sourcing from non‐local organizations may be more important for supporting innovation in rural compared to urban markets. [ABSTRACT FROM AUTHOR]

Information controls are actions intended to deny, disrupt, monitor, or secure information for political ends. They can be implemented using a wide variety of technical and nontechnical means. Political contests over the control of information are heightened around important events, such as major anniversaries, armed conflicts, protests, and elections. In this paper, we offer a comparative case study of online censorship of the circumvention tool Psiphon during the Iranian elections in 2016 and 2013, drawing on unique access to analytics data from Psiphon. We find that the Iranian regime developed its censorship approach in two ways, deploying blocking that was more targeted and strategically timed in the more recent case. Evidence suggests that the regime relaxed censorship of Psiphon during the official campaign period for the 2016 election. The apparent objective of this new approach was to control access to information while minimizing the political consequences of doing so. [ABSTRACT FROM AUTHOR]