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The use of structured query formulation languages is a method for gaining access to data in information management systems. Writing structured queries is a powerful method of data retrieval, and end users can generate complex database queries by becoming proficient in a particular query language. Digitization of database information systems, history and endowment, and technology conservation are some examples of database conservation techniques in the process of displaying data that require optimal query techniques. Historical and endowment properties comply with a certain set of laws governing waqf recipients, which sets them apart from heritage and cultural assets. Trusted property typically comprises real estate, valuables, or both and has an infinite preservation term so long as it may still be put to use. A solid information technology infrastructure is essential for ensuring comprehensive data security. Given the availability of knowledge and the quick development of information technology, ensuring its sustainability is a challenge. This research is aimed at preserving historical and waqf databases based on the case study of the Kingdom of Sumedang Larang (KSL), Indonesia, through examination of the database, synchronization of digital data with physical data, as well as looking at its relationship with organizations and management. The proposed method, namely the Design and Analysis of Database Query Model for Preservation Information System (DAQMP), creates a recurring query model from the original tabular data placed in the next table as a special table check for data specifications containing important data. The results must be accurately aligned between digital and physical records regularly to serve as a record of any changes and as evidence to determine whether data has been corrupted, altered, or lost. [ABSTRACT FROM AUTHOR]

Technology to enable and support learning and teaching is widespread in university settings. One consequence of such technology use is the accumulation of large volumes of digital data. The acquisition of, and failure to, discard digital content can lead to digital clutter. The potential negative consequences of digital clutter have been examined mainly within a workplace context. Far less is known about how university students manage their academic digital data and whether they have strategies to deal with excessive digital clutter. Eighteen undergraduate students took part in a one-to-one or group-based interview to discuss their digital data management strategies including accumulation and deletion behaviours. Thematic analysis led to three themes: (1) Digital data accumulation across the student journey, (2) Reactive and evolving digital data management strategies and (3) Data overload: Anxiety, loss of productivity and feeling overwhelmed. The findings capture the complexity of feelings students have about different types of digital technology and the strategies they use to manage increasingly large volumes of digital data. Findings are discussed in relation to the need for better support and guidance for students around the use of digital technology to manage their data during their time at university. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Online wildlife trade is widespread and affects thousands of species. Yet, attempts to quantify online wildlife trade have mainly focused on a few platforms and taxonomic groups. Here, we study the prevalence of wildlife trade using automated data collection and filtering methods. We analyze trade across five digital platforms and 156 animal and plant species of conservation concern from a global biodiversity hotspot, the Philippines. We identified approximately 5000 highly relevant instances of trade in 1.47 million posts, focusing on 108 species, 79 of which are classified as threatened. Trade mainly occurred on webpages indexed in Google and on Twitter. We found that manual validation is essential, as animals obtained a higher proportion of hits prior to validation. Following manual validation, we observed a shift toward plant‐related trade hits. Scaling up these approaches to a global level is key to understanding the extent of digital wildlife trade across the globe. [ABSTRACT FROM AUTHOR]

The article discusses the need to adopt digital tools for monitoring the social dimensions of the global biodiversity framework. The current monitoring framework has gaps, particularly in tracking human attitudes and behaviors towards species and biodiversity. Integrating social indicators into ecological indicators can provide valuable insights and conservation potential. The article highlights the importance of readily available and up-to-date social indicators in designing effective and ethically permissible conservation practices. The increased access to the internet and advances in technology allow for real-time monitoring and analysis of attitudes and behaviors towards biodiversity. However, it is important to address disparities in internet access and consider cultural and social biases in data collection and analysis. Overall, integrating social indicators into the monitoring framework can help drive conservation efforts and promote the recovery of biodiversity. [Extracted from the article]

Using traces of behaviors to predict outcomes is useful in varied contexts ranging from buyer behaviors to behaviors collected from smart-home devices. Increasingly, higher education systems have been using Learning Management System (LMS) digital data to capture and understand students' learning and well-being. Researchers in the social sciences are increasingly interested in the potential of using digital log data to predict outcomes and design interventions. Using LMS data for predicting the likelihood of students' success in for-credit college courses provides a useful example of how social scientists can use these techniques on a variety of data types. Here, we provide a primer on how LMS data can be feature-mapped and analyzed to accomplish these goals. We begin with a literature review summarizing current approaches to analyzing LMS data, then discuss ethical issues of privacy when using demographic data and equitable model building. In the second part of the paper, we provide an overview of popular machine learning algorithms and review analytic considerations such as feature generation, assessment of model performance, and sampling techniques. Finally, we conclude with an empirical example demonstrating the ability of LMS data to predict student success, summarizing important features and assessing model performance across different model specifications. [ABSTRACT FROM AUTHOR]

Cloud computing has gained considerable attention in academia and industry in recent years. The cloud facilitates data sharing and enables cost efficiency, thus playing a vital role today as well as for the foreseeable future. In this paper, a brief discussion the application of multi-tenant and load-balancing technologies to cloudbased digital resource sharing suitable for academic and digital libraries is presented. As a new paradigm for digital resource sharing, a proposal of improving the current user service model with private cloud storage for other sectors, including the medical and financial fields is offered. This paper gives a summary of cloud computing and its possible applications, combined with digital data optimisation for web-based services. This study could aid in identification and generation of cloud-based services that use multi-tenant and load-balancing methodologies for the best quality of service. [ABSTRACT FROM AUTHOR]

Purpose: The impact of innovative web portals on users, from access to application, is gaining interest as the global call for increased data availability gains momentum. This study reports on the perceptions of portal end users about usage and access to digital data across a range of fields of practice. Design/methodology/approach: Data were collected and analysed from interviews (n = 132) and email feedback (n = 235) from end users of interoperable spatial knowledge web portals. Findings: Data reveal that users attribute importance to ease of access and applicability, and to confidence and trust in data. The acquisition of data assists with reducing knowledge silos, facilitates knowledge sharing and decision-making. Digital data portals enable the building of stronger collaborations between different groups of individuals and communities leading to improved outcomes and more positive developments across varied discipline and practice areas. Practical implications: Recommendations for developing online portals to optimise knowledge transfer and associated benefits, for users, are offered. Originality/value: By collecting extensive qualitative data drawn from the experiences of end users of digital data portals, this paper provides new insights, thereby addressing a knowledge gap in the published literature about the use of technology uptake and the application of online data for practice and industry benefit. [ABSTRACT FROM AUTHOR]

Purpose: The Alabama Department of Public Health (ADPH) sponsored a TikTok contest to improve vaccination rates among young people. This analysis sought to advance understanding of COVID-19 vaccine perceptions among ADPH contestants and TikTok commenters. Approach: This exploratory content analysis characterized sentiment and imagery in the TikTok videos and comments. Videos were coded by two reviewers and engagement metrics were collected for each video. Setting: Publicly available TikTok videos entered into ADPH's contest with the hashtags #getvaccinatedAL and #ADPH between July 16 – August 6, 2021. Participants: ADPH contestants (n = 44) and TikTok comments (n = 502). Method: A content analysis was conducted; videos were coded by two reviewers and engagement metrics was collected for each video (e.g., reason for vaccination, content, type of vaccination received). Video comments were analyzed using VADER, a lexicon and rule-based sentiment analysis tool). Results: Of 44 videos tagged with #getvaccinatedAL and #ADPH, 37 were related to the contest. Of the 37 videos, most cited family/friends and civic duty as their reason to get the COVID-19 vaccine. Videos were shared an average of 9 times and viewed 977 times. 70% of videos had comments, ranging from 0-61 (mean 44). Words used most in positively coded comments included, "beautiful," "smiling face emoji with 3 hearts," "masks," and "good.;" whereas words used most in negatively coded comments included "baby," "me," "chips," and "cold." Conclusion: Understanding COVID-19 vaccine sentiment expressed on social media platforms like TikTok can be a powerful tool and resource for public health messaging. [ABSTRACT FROM AUTHOR]

Amid the ongoing pandemic and the so-called 'New Cold War,' physical mobility dwindles and political paranoia surges. China has been increasingly portrayed as a 'black box' in anglophone discourse, scholarly and popular alike. More than ever, digital platforms serve as the sites and means to know 'the Chinese reality.' In this paper, we mobilize insights from Science and Technology Studies (STS), especially its epistemological and ontological reflections on the 'black box' metaphor, to confront the ongoing 'blackboxing' of China and, in tandem, the embrace of digital platform data as 'open source' to penetrate China from afar. Foregrounding the role of technological infrastructures, research positionality, and power relations in knowledge production, we situate this phenomenon in broader shifts in geopolitics and academic ecology. We then suggest alternative routes for empirical investigation: (1) to reembed Chinese platform data in their sociotechnical contexts, (2) to approach a 'networked China' at and across different scales, and relatedly, (3) to attune to obscured positionalities in fieldwork and analysis. Ultimately, we urge communities of China researchers to attend to the politics and materiality of knowledge production and resist the pervading 'New Cold War' framing. [ABSTRACT FROM AUTHOR]

The handling of a tunnel construction project poses great challenges for all those involved. Variables that cannot be clearly quantified can arise during the entire process of the project. The subsoil in tunnelling is one of these parameters which is difficult to forecast. The geological and hydrogeological conditions must be assessed during the planning phase with the help of exploratory measures and from the experience from projects that have already been built. During the execution work, deviations from the documents on which the target determination is based occur in almost all underground construction projects. These changes can either cause a change in the construction process and/or lead to a different construction time in relation to the calculated duration. Based on this initial situation, the development of an innovative contract and remuneration model for machine tunnelling appears to be important. The main focus of the model is to generate a transparent and comprehensible method of how the remuneration‐worthy portion can be calculated in the case of a different construction time in mechanised tunnelling. In order to ensure this transparency and traceability of the system to be developed, the data records that can be digitally recorded during the tunnelling work are used as a fundamental basis for the created model. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Drawing from feminist contributions in data studies and pedagogy, this article develops the notion of data-caring as an ethico-political intervention. It interrogates the way the 'digital architecture of neoliberalism' reduces the complexity of social relations and looks at the absence of conversations and narratives. Against the background of political polarization in Brazil, the article discusses how datafying practices in the digital world enact categories that identify Self and Other without context or complexity. In opposition, data-caring is based on the understanding that the kind of dialogue necessary to live together in polarized times requires conversations that can decompress narrative arcs. As we approach new elections, I detail the experience of teaching an experimental course after the 2018 elections in Brazil and offer insights about what constituted an exploratory study in data-caring, where we explored how we can care about data, care with data and datafy with care. [ABSTRACT FROM AUTHOR]

The essay proposes to use alienation as a heuristic and conceptual tool for the analysis of the impact of digital information and communication technologies (ICTs) on users. It follows a historical materialist understanding, according to which data can be considered as things produced in an industrial fashion. A representational interpretation, according to which data would merely reflect a given reality, is untenable. It will be argued instead to understand data as an additional layer which has a transformative impact on reality as a whole. The analysis follows the early Marx in thinking of alienation as a structural condition which holds even if it is not experienced psychologically by users. Alienation means that the desire to express oneself and achieve social recognition, self-realization, and participation through the use of ICTs is incongruent to the inherent purposes and functions of these technologies. Digital platforms create the ideological illusion that users contribute to the production of data solely for their own gratification. Users, in turn, react to structural alienation either by internalizing it, in which case they may become enthusiastic data producers, or by imposing alienating conditions on other users. Finally, it will be shown that a strong notion of privacy is less suited to articulate concerns about the impact of ICTs because it expresses a desire for privilege and individual control which has become unfulfillable in the environment of data industries. The essay closes by showing some of the changes in institutional structures and behavior that could follow from the focus on alienation. [ABSTRACT FROM AUTHOR]

Building on a unified definition and the main attributes that have been identified for platform business models, this paper aims to devise a unified data value chain and shed a new light on the value creation process within platform business models. To meet the main aim of the paper, the following research question is addressed: "How do platform business models create, deliver and capture value through their business model configurations?". Through an integrative literature review, this paper confirmed that data is the major asset in value creation through platform business models. Furthermore, this paper has devised a unified data value chain that encompasses sequential forms of digital data such as raw data, pre-processed data, processed data, patterns, and smart data, gaining value via numerous processes throughout the data value chain. It was highlighted that interlinked processes throughout the data value chain transformed raw data into the most valuable form of data, knowledge. [ABSTRACT FROM AUTHOR]

In this article, we present ideas about developing innovative methods for the sociology of futures. Our approach brings together the literature on sociotechnical imaginaries and the sociology of futures with vital materialism theories and research-creation methods. We draw on our research-creation materials from a series of online workshops. The workshops involved the use of creative writing prompts with participants across a diverse range of age groups and locations. The article ends with some reflections on the implications of our approach for researching the futures of emerging digital technologies and the methodological and theoretical development of the sociology of futures. [ABSTRACT FROM AUTHOR]

The AI and Society discourse has previously drawn attention to the ways that digital systems embody the values of the technology development community from which they emerge through the development and deployment process. Research shows how this effect leads to a particular treatment of gender in computer systems development, a treatment which lags far behind the rich understanding of gender that social studies scholarship reveals and people across society experience. Many people do not relate to the narrow binary gender options of male or female, and many people express their gender identity in much richer ways than the sex/gender binary female/woman and male/man Boolean terms will allow. We ask: are "born-digital" gendered datasets in digital systems experienced as marginalising by those who express their identity beyond the male/female binary? Case Study: Ireland. To answer this universal question, this paper presents the findings of an empirical case study of people in Ireland with diverse gender identities and expressions, and their experiences with public data systems and new technologies. In spite of great social changes in Ireland which have led to constitutional change in favour of LGBTQI + people, born-digital systems were experienced by respondents as embodying socio-cultural values which were no longer accepted in society at large. For many of the respondents, digital technologies routinely marginalise them in all kinds of ways. These systems keep alive violence and oppression long after civil rights have been enshrined in constitutional law. This study is just one example of the way assumptions about digital are disengaged from society-at-large. It is a call to arms to all who are passionate about socially-responsible technology. [ABSTRACT FROM AUTHOR]

A key functionality of Integrated Earthquake Simulation which carries out regional earthquake simulations is automated model construction that builds a set of analysis models for different numerical analysis methods, using a variety of data which cover city and urban areas. Engineering information such as design codes and regulations of the structure is systematically used to make up for the lack of the digital data. Explanation is made about the developed methodology and algorithms of the automated model construction for two kinds of structures: residential buildings and road bridges. [Extracted from the article]

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that results in altered behavior, social development, and communication patterns. In recent years, autism prevalence has tripled, with 1 in 44 children now affected. Given that traditional diagnosis is a lengthy, labor-intensive process that requires the work of trained physicians, significant attention has been given to developing systems that automatically detect autism. We work toward this goal by analyzing audio data, as prosody abnormalities are a signal of autism, with affected children displaying speech idiosyncrasies such as echolalia, monotonous intonation, atypical pitch, and irregular linguistic stress patterns. Objective: We aimed to test the ability for machine learning approaches to aid in detection of autism in self-recorded speech audio captured from children with ASD and neurotypical (NT) children in their home environments. Methods: We considered three methods to detect autism in child speech: (1) random forests trained on extracted audio features (including Mel-frequency cepstral coefficients); (2) convolutional neural networks trained on spectrograms; and (3) fine-tuned wav2vec 2.0—a state-of-the-art transformer-based speech recognition model. We trained our classifiers on our novel data set of cellphone-recorded child speech audio curated from the Guess What? mobile game, an app designed to crowdsource videos of children with ASD and NT children in a natural home environment. Results: The random forest classifier achieved 70% accuracy, the fine-tuned wav2vec 2.0 model achieved 77% accuracy, and the convolutional neural network achieved 79% accuracy when classifying children’s audio as either ASD or NT. We used 5-fold cross-validation to evaluate model performance. Conclusions: Our models were able to predict autism status when trained on a varied selection of home audio clips with inconsistent recording qualities, which may be more representative of real-world conditions. The results demonstrate that machine learning methods offer promise in detecting autism automatically from speech without specialized equipment. [ABSTRACT FROM AUTHOR]

Résumé: 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. [ABSTRACT FROM AUTHOR]

Depression is one of the major mental health problems in the world and the leading cause of disability worldwide. As people leave more and more digital traces in the online world, it becomes possible to detect depression-related behavior based on people's online activities. We use a novel Facebook study to identify possible non-textual elements of depression-related behavior in a social media environment. This study focuses on the relationship between depression and the volume and composition of Facebook friendship networks and the volume and temporal variability of Facebook activities. We also tried to establish a link between depression and the interest categories of the participants. The significant predictors were partly different for cognitive-affective depression and somatic depression. Earlier studies found that depressed people have a smaller online social network. We found the same pattern in the case of cognitive-affective depression. We also found that they posted less in others' timelines, but we did not find that they posted more in their own timeline. Our study was the first to use the Facebook ads interest data to predict depression. Those who were classified into the less interest category by Facebook had higher depression levels on both scales. [ABSTRACT FROM AUTHOR]

Understanding people's movement patterns has many important applications, from analyzing habits and social behaviors, to predicting the spread of disease. Information regarding these movements and their locations is now deeply embedded in digital data generated via smartphones, wearable sensors, and social-media interactions. Research has largely used data-driven modeling to detect patterns in people's movements, but such approaches are often devoid of psychological theory and fail to capitalize on what movement data can convey about associated thoughts, feelings, attitudes, and behavior. This article outlines trends in current research in this area and discusses how psychologists can better address theoretical and methodological challenges in future work while capitalizing on the opportunities that digital movement data present. We argue that combining approaches from psychology and data science will improve researchers' and policy makers' abilities to make predictions about individuals' or groups' movement patterns. At the same time, an interdisciplinary research agenda will provide greater capacity to advance psychological theory. [ABSTRACT FROM AUTHOR]

In this paper, we present our experience designing and implementing a hybrid citizen science protocol combining local data collection reported digitally with the return of physical samples by mail. Our project, Fossil Atmospheres, housed within the Paleobiology Department of the Smithsonian Institution's National Museum of Natural History, sought to complete a broad geographic collection of Ginkgo biloba L. leaves to better understand climate change over time. We also wished to leverage and test the affordances of using an established online platform as a technological tool for research-quality data collection. Participants were asked to find a local ginkgo tree and, using a hybrid protocol, collect leaf samples and record site data, including photos, GPS coordinates, and tree characteristics, using the iNaturalist online platform. Participants then returned their leaf samples by mail. Fossil Atmospheres received 562 leaf samples from 352 participants. These samples, representing 36 states, met our target geographic transects and reflected the known habitat range of living ginkgo in the United States. We were able to successfully pair a large majority of received samples to their corresponding digital data records, allowing us to include 88% of the samples received within the Fossil Atmospheres data set. These results greatly exceeded our project goals. The hybrid protocol model we present, based on our experiences, indicates that using tools like iNaturalist provides multiple benefits that meet or exceed more traditional data collection models, including increases in the scale of data that can be collected, data accuracy, and data completeness, uniformity, usability, and accessibility. [ABSTRACT FROM AUTHOR]

Depuis quelques temps émerge l'idée que le développement de l'intelligence artificielle et l'ouverture prochaine des données judiciaires permettront, à partir de l'analyse des décisions passées, d'anticiper la décision judiciaire à venir. Les promoteurs de ce qu'on appelle ainsi la justice prédictive soutiennent qu'en améliorant la prévisibilité de la jurisprudence, celle-ci permettra non seulement de sécuriser l'action en justice, mais aussi de favoriser le recours aux modes alternatifs de règlement des différends. Si l'arrivée prochaine de ces outils est inéluctable, elle n'est cependant ni sans danger ni sans limites. For some time now, the idea has emerged that the development of artificial intelligence and the forthcoming opening of judicial data will make it possible, based on the analysis of past decisions, to anticipate an upcoming judicial decision. The promoters of what is called predictive justice argue that by improving the predictability of case law, it will not only secure legal action, but also promote the use of alternative dispute resolution methods. While the imminent arrival of these tools is inevitable, it is neither without danger nor without limits. [ABSTRACT FROM AUTHOR]

This research note introduces the experience of using ‘timelines’ as a visual research method during online interviewing. It does so through a series of questions and answers that guide the reader through an exploration, understanding of and reflection on the method. This qualitative approach was used while conducting research on the influence that participation in a Reality TV show had on its finalists, and on the opportunities and life choices that were afforded to participants after the end of the show. The reader is encouraged to draw links between their own work as a qualitative researcher and the possibilities that this method can offer either in filling gaps or in expanding their current endeavour. Ultimately, the ‘quality’ of the answers we find in our qualitative work is illustrative of the way we choose to ask our questions. [ABSTRACT FROM AUTHOR]

Stage of networking is quintessential task in which security comes into play. Securing these networks which contains confidential digital data that needs to secured will be the agenda of cryptography. Many cryptographic algorithms increment their strengths over parameters like key size, increasing the rounds of iteration and finally using confusion box as S-box as it has best robustness. So, this paper mainly focusses over securing digital data with the help of S-box function over Data Encryption Standard (DES) algorithm. For this, a plain text and key will be given to this DES as it extracts 8x8(64) bit characters from the key and converting them into its corresponding ASCII value and are concatenating to form an 8 value by taking mod16. These will give to 8 S-box in order to generate its corresponding output to make even more secure and also shows dynamic DES gives much result than other crypto methods. The evaluation of this integrated s-box and DES shows much fruitful results over factors like non-linearity, Avalanche criterion, Balance, Robustness to linear cryptanalysis, Robustness to differential cryptanalysis. [ABSTRACT FROM AUTHOR]

The education sector is fast digitalising all of its operations. A large part is driven by proprietary digital products and services developed and offered by for-profit companies that form the education technology industry. This article aims to introduce a theoretical focus of rentiership and assetization into the study of the political economy of education technology. It discusses five potential transformations that the education sector is undergoing as a consequence of digital rentiership. These transformation address new rentee and potential rentier roles of education institutions, nestedness of digital platforms and their terms of use, a rise of contractual governance within the education sector, re-institutionalising the sector, and tensions between competition and monopoly in digital education markets. These trends are not exhaustive and represent only the start of the analysis on rentiership in education. The paper concludes with an invitation for future research. [ABSTRACT FROM AUTHOR]

Digital data (internet queries, page views, social media posts, images) are accumulating online at increasing rates. Tools for compiling these data and extracting their metadata are now readily available. We highlight the possibilities and limitations of internet data to reveal patterns in host–parasite interactions and encourage parasitologists to embrace iParasitology. [ABSTRACT FROM AUTHOR]

Aim: To evaluate techniques for assessing soft tissue alterations at implant sites and compare the traditionally utilized methods to the newer three‐dimensional technologies emerging in the literature. Materials and Methods: A comprehensive search was performed to identify interventional studies reporting on volumetric changes at implant sites following different treatments. Results: Seventy‐five articles were included the following: 30 used transgingival piercing alone, one utilized calliper, six with ultrasonography, six on cone‐beam computed tomography, and 32 utilized optical scanning and digital technologies. Optical scanning‐based digital technologies were the only approach that provided 'volumetric changes,' reported as volumetric variation in mm3, or the mean distance between the surfaces/mean thickness of the reconstructed volume. High variability in the digital analysis and definition of the region of interest was observed. All the other methods reported volume variation as linear dimensional changes at different apico‐coronal levels. No studies compared volumetric changes with different approaches. Conclusions: Despite the emergence of optical scanning‐based digital technologies for evaluating volumetric changes, a high degree of variation exists in the executed workflow, which renders the comparison of study results not feasible. Establishment of universal guidelines could allow for volumetric comparisons among different studies and treatments. [ABSTRACT FROM AUTHOR]

It is often claimed that the rise of so called 'big data' and computationally advanced methods may exacerbate tensions between disciplines like data science and anthropology. This paper is an attempt to reflect on these possible tensions and their resolution, empirically. It contributes to a growing body of literature which observes interdisciplinary collabrations around new methods and digital infrastructures in practice but argues that many existing arrangements for interdisciplinary collaboration enforce a separation between disciplines in which identities are not really put at risk. In order to disrupt these standard roles and routines we put on a series of workshops in which mainly self-identified qualitative or non-technical researchers were encouraged to use digital tools (scrapers, automated text analysis and data visualisations). The paper focuses on three empirical examples from the workshops in which tensions, both between disciplines and between methods, flared up and how they were ultimately managed or settled. In order to characterise both these tensions and negotiating strategies I draw on Woolgar and Stengers' use of the concepts humour and irony to describe how disciplines relate to each others' truth claims. I conclude that while there is great potential in more open-ended collaborative settings, qualitative social scientists may need to confront some of their own disciplinary baggage in order for better dialogue and more radical mixings between disciplines to occur. [ABSTRACT FROM AUTHOR]

Il paraît légitime de s'interroger sur l'influence que pourraient prendre les technologies numériques sur le champ instable des classifications psychiatriques. À titre d'exemple, le recueil passif de données constitue une forme de monitoring semblant privilégier les approches dimensionnelles, plus à même de rendre compte d'évolutions cliniques marquées par des tendances globales ou des ruptures, mais difficilement accordable avec une classification catégorielle. L'enthousiasme autour de ces technologies reste à recontextualiser, et une anticipation réaliste de leur utilisation à court terme nous paraît plus se rapprocher d'une assistance numérique, nécessitant le développement d'une nouvelle forme d'éducation thérapeutique, l'éducation à la gestion de ses données de santé. It seems legitimate to wonder about the influence that digital technologies could have on the unstable field of psychiatric classifications. For example, passive data collection is a form of monitoring that seems to promote dimensional approaches, more able to represent global trends or breaks than categorial classification based on symptomatology. The enthusiasm around these technologies needs to be recontextualized, and a realistic short-term development could lead to a form of digital assistance, requiring the development of a new type of therapeutic education: personal health data management. [ABSTRACT FROM AUTHOR]

Indigenous food sovereignty and security are essential to Indigenous health and cultural perpetuity. Revitalization of traditional foodways can counteract the negative impacts of colonial food practices and policies on the health of Indigenous peoples. A mixed methods survey was conducted to describe the data needs of people working in Indigenous nutrition related fields. Results showed that nutrition education, academic scholarship, and community projects were the most frequently used data categories. With improved access, projects-in-progress and raw data would be utilized for reference and staying current. The most common barrier was not knowing where or how to access information. Raw research data, research, projects-in-progress, and tribal policy were the most difficult to access. The study concludes that an online Food Wisdom Repository can contribute to health equity by improving access to Indigenous knowledge and wise practices, cultivating culturally appropriate data sharing, and sustaining and extending current work in the field. [ABSTRACT FROM AUTHOR]

This paper critically explores the research and development of 'digital phenotyping', which broadly refers to the idea that digital data can measure and predict people's mental health as well as their potential risk for mental ill health. Despite increasing research and efforts to digitally track and predict ill mental health, there has been little sociological and critical engagement with this field. This paper aims to fill this gap by introducing digital phenotyping to the social sciences. We explore the origins of digital phenotyping, the concept of the digital phenotype and its potential for benefit, linking these to broader developments within the field of 'mental health sensing'. We then critically discuss the technology, offering three critiques. First, that there may be assumptions of normality and bias present in the use of algorithms; second, we critique the idea that digital data can act as a proxy for social life; and third that the often biological language employed in this field risks reifying mental health problems. Our aim is not to discredit the scientific work in this area, but rather to call for scientists to remain reflexive in their work, and for more social science engagement in this area. [ABSTRACT FROM AUTHOR]

A spate of recent scandals concerning personal digital data illustrates the extent to which innovation and finance are thoroughly entangled with one another. The innovation-finance nexus is an example of an emerging dynamic in technoscientific capitalism in which innovation is increasingly driven by the pursuit of "economic rents". Unlike innovation that delivers new products, services, and markets, innovation as rentiership is defined by the extraction and capture of value through different modes of ownership and control over resources and assets. This shift towards rentiership is evident in the transformation of personal digital data into a private asset. In light of this assetization, it is necessary to unpack how innovation itself might be a problem, rather than a solution to a range of global challenges. Our aim in this paper is to conceptualize this relationship between innovation, finance, and data rentiership, and examine the policy implications of this pursuit of economic rents as a deliberate research and innovation strategy in data-driven technology sectors. [ABSTRACT FROM AUTHOR]

Digital data are accumulating at unprecedented rates. These contain a lot of information about the natural world, some of which can be used to answer key ecological questions. Here, we introduce iEcology (i.e., internet ecology), an emerging research approach that uses diverse online data sources and methods to generate insights about species distribution over space and time, interactions and dynamics of organisms and their environment, and anthropogenic impacts. We review iEcology data sources and methods, and provide examples of potential research applications. We also outline approaches to reduce potential biases and improve reliability and applicability. As technologies and expertise improve, and costs diminish, iEcology will become an increasingly important means to gain novel insights into the natural world. iEcology is a new research approach that seeks to quantify patterns and processes in the natural world using data accumulated in digital sources collected for other purposes. iEcology studies have provided new insights into species occurrences, traits, phenology, functional roles, behavior, and abiotic environmental features. iEcology is expanding, and will be able to provide valuable support for ongoing research efforts, as comparatively low-cost research based on freely available data. We expect that iEcology will experience rapid development over coming years and become one of the major research approaches in ecology, enhanced by emerging technologies such as automated content analysis, apps, internet of things, ecoacoustics, web scraping, and open source hardware. [ABSTRACT FROM AUTHOR]

Advances in information and communication technologies have enabled health care users and providers to share health information online thus generating contents, which may be used for health-related research. In addition, the data may be used for health care decision-making thus blurring the boundaries between health care and research particularly with the repurposing of data for other uses. This paper discusses the ethical and legal concerns that emerge from using digital data from user-generated online health content for health-related research. It analyses the nature of digital health data from user-generated online content and considers the extent to which its use can be governed through the current regulatory and ethical frameworks. It then highlights the strengths and weaknesses of these frameworks and proposes strategies that can be used to protect data subjects' privacy while facilitating research in an ethical manner. [ABSTRACT FROM AUTHOR]

Health-related information is increasingly being collected and stored digitally. These data, either structured or unstructured, are becoming the ubiquitous assets that might enable us to comprehensively map out a patient's health journey from an asymptomatic state of wellness to disease onset and its trajectory. These new data could provide rich real-world evidence for better clinical care and research, if they can be accessed, linked and analyzed—all of which are possible. In this review, these opportunities will be explored through a case vignette of a patient with OA, followed by discussion on how this digitalized real-world evidence could best be utilized, as well as the challenges of data access, quality and maintaining public trust. [ABSTRACT FROM AUTHOR]

Latour's notion of immutable mobiles relates the circulability of certain objects to, among other features, their immutability, readability and combinability. As such it does not distinguish between, say, hand-drawn maps and machine-generated graphs. How, though, does the medial 'microstructure' of immutable mobiles matter to socially shared uses? Would, for example, digital images as bounded grids of nonoverlapping square pixels, each representing a numerical value, shape how distributed scientific work unfolds? In this article, I begin with reviewing attempts to link the microstructure of media to their communicative uses, focusing on Luhmann's relational account of media as loosely coupled substrates in which more rigid forms can become manifest. Drawing on an ethnography of astronomical research, I then inquire into how the scientists involved reasoned about their uses of media from within their practices. They used digital photographic exposures as 'workable objects' whose usefulness was not guaranteed initially. Local work was oriented to potential reuses of images (as processed exposures) by researchers elsewhere, as demonstrated by concerns over the integrity of images, the possibility of describing their work with reasonable efforts, as well as by negotiating acceptable elements in calculations so as to reveal stabilized phenomena. In doing so, scientists insisted on the need to play or experiment, suspending sequential work for explorations oriented toward deciding which action among alternatives to make consequential. This was part of a more extended 'calculative game' that points, through its orientation to reasonable agreement and delimitations of legitimate efforts, to the social order of this work. The medium, here conceived as images deemed accountable to reuses elsewhere, is a social achievement. Recognizing this may help to better understand the reusability of scientific data and its challenges. [ABSTRACT FROM AUTHOR]

Objectives of business sustainability efforts commonly include increasing consumer safety, decreasing resource consumption, and decreasing pollution. Even though there is a societal interest in attaining these goals, business and other economic agents often operate under incentive structures that run counter to these objectives. Taxi drivers operate as economic independents. Their revenue depends on their fares and tips. Moreover they choose how many hours to work, how fast to drive, and which route to take. Using New York City taxi data from 2013, we test the level of alignment between the revenue maximizing behavior of drivers versus safety, conservation and pollution-related outcomes that are valued by stakeholders. We find substantial misalignment—i.e., in order to maximize revenue, drivers take inefficient routes and they exceed the speed limit thus decreasing safety, increasing fuel consumption and increasing air pollution. Based on these empirical results, we suggest methods of aligning societal goals with those of revenue maximizing taxi drivers. • Speeding drivers killed 9262 people in 2014. • The economic impact of speeding averages about $40.4 billion a year in the United States. • Multiple regression supports the idea that taxi drivers make more money by speeding. • Regression results support the notion that taking a longer route increases driver revenue. • Auto shutoff taxi meters would reduce taxi speeding, reducing deaths and damages to society. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In 1989, New Zealand started to follow an international trend of reforming education policy according to the neoliberal principles of competition, choice and self-managing schools. Since then, the increasing availability of digital data in schools has corresponded with the development of student achievement measurement tools and benchmarking of standards that enable comparison of schools and cohorts of students. More recently, national policy targets for student achievement have been introduced and form the basis of accountability measures. The article uses Hargreaves and Shirley's 'Four Ways' characterisation of education policy change as a framework to examine the influence that national policy has had on the use of data, on power relations between schools and the national policymakers, and on the challenges faced by school leaders. Interviews in 16 schools explored the types of data available in each school, how they are used and how principals, as leaders in these self-managing schools, would like to be able to use the data. Two systemic influences explain the patterns found in the research. The first is the tension principals face between data required for accountability reporting and data needed for school-based decision-making. The second is the issue with regard to economies of scale and marketisation of education that affects equitable access to the knowledge, tools and expertise that enable effective data usage. [ABSTRACT FROM AUTHOR]

The knowledge infrastructures of the sciences have been considered as human-made networks or ecologies of people, artifacts, and institutions that enable the production, calibration, storage, dissemination and re-use of data. Complementing these studies, this paper examines how scientists use the digitally mediated, shared availability of "natural" environments and objects for infrastructural purposes. Drawing on ethnography and informed by ethnomethodology, I focus on the uses of the sky in astronomical observation. Astronomical research is oriented to observing, and re-observing, sources on the sky, making it its topic. Yet, the sky is also an infrastructural resource, as it provides stable saliences that can be used alongside existing records for ordering work, diagnosing trouble with artifacts in data, and repairing data across diverse sites of practice. I consider a case in which such uses of the sky were new to researchers working in a novel domain, and one in which such uses were already established, but new to a student being inducted to its work. In both cases properties of the sky became salient through being mediated digitally. As existing records and new observations were made available to a single computational order, these data became accessible to what Melvin Pollner called mundane reason, wherein ceteris paribus clauses are used reflexively to maintain a world in common. Although the sky may appear to be an extreme case, I argue that other mediated environments and objects, and the reflexive practices through which these are engaged, have similar infrastructural uses in other disciplines. [ABSTRACT FROM AUTHOR]

The first two decades of the twenty-first century have seen a rapid rise in the mobilization of digital biodiversity data. This has thrust natural history museums into the forefront of biodiversity research, underscoring their central role in the modern scientific enterprise. The advent of mobilization initiatives such as the United States National Science Foundation's Advancing Digitization of Biodiversity Collections (ADBC), Australia's Atlas of Living Australia (ALA), Mexico's National Commission for the Knowledge and Use of Biodiversity (CONABIO), Brazil's Centro de Referência em Informação (CRIA) and China's National Specimen Information Infrastructure (NSII) has led to a rapid rise in data aggregators and an exponential increase in digital data for scientific research and arguably provide the best evidence of where species live. The international Global Biodiversity Information Facility (GBIF) now serves about 131 million museum specimen records, and Integrated Digitized Biocollections (iDigBio) in the USA has amassed more than 115 million. These resources expose collections to a wider audience of researchers, provide the best biodiversity data in the modern era outside of nature itself and ensure the primacy of specimen-based research. Here, we provide a brief history of worldwide data mobilization, their impact on biodiversity research, challenges for ensuring data quality, their contribution to scientific publications and evidence of the rising profiles of natural history collections. [ABSTRACT FROM AUTHOR]

Laboratory ethnographies have emphasized the importance of trust and accountability among scientists and technicians when working in co-presence. But what happens to their relations when data production is outsourced, widely separating scientists and technicians? In contemporary astronomy, observing has largely become a service that observatory staff members do for researchers. This has increased the efficiency of telescope use while also resulting in arrangements prone to some researchers' dissatisfaction and a raised visibility of technicians' work. Attending ethnographically to situated evaluations reveals that some data-using researchers and data-producing technicians typify each other as moral figures: staff observers come to be seen as objects of blame and scientists as excessively demanding users. Wherever data travel, the quality and quantity of data can serve as ethical affordances for assigning blame to staff technicians. By contrast, the moral figure of the excessively demanding data user does not travel beyond the observatory, and the social accountability of interactions that visiting astronomers experience in the observatory's control room is confined to its situated enactment. As scientist-technician interactions have become discontinuous and fraught, moral figures and ethical accounts thus travel unevenly in the landscape of data production, and the importance of social interactions remains often unrecognized. [ABSTRACT FROM AUTHOR]

Background: Personal health data (PHD) research has been intensified over the last years, attracting the attention of scientists from different fields, such as software engineers, computer scientists and medical professionals. The increasing interest of researchers can be attributed to the exponential growth of the available PHD due to the widespread adoption of ubiquitous technology in everyday life, as well as to the potential of the ongoing digital transformation in healthcare. This increasing interest requires that academia has an overview of the published scientific literature to plan future endeavors.Objective: The main objective of this study is to identify and address research gaps in literature regarding PHD.Method: This paper conducts a systematic mapping study to summarize the existing PHD approaches in literature and to organize the selected studies according to six classification criteria: publication source, publication year, research types, empirical types, contribution types and research topic.Results: In total 79 papers have been included after fulfilling the inclusion criteria and have been classified accordingly. There is an increasing amount of attention that has been paid to PHD since 2014. The majority of papers is published in journals. The two main research types found were solution proposals and evaluation research. The majority of the selected papers were empirically evaluated. The main contribution types were methods and frameworks. Data privacy is the most frequently addressed topic in PHD literature, followed by data sharing.Conclusions: The findings of this systematic mapping study have implications for both researchers who are planning new studies in PHD and for practitioners who are working in connected health and would like to have an overview on the existent studies on PHD research area. [ABSTRACT FROM AUTHOR]

The digital traces that we leave online are increasingly fruitful sources of data for social scientists, including those interested in demographic research. The collection and use of digital data also presents numerous statistical, computational, and ethical challenges, motivating the development of new research approaches to address these burgeoning issues. In this article, we argue that researchers with formal training in demography-those who have a history of developing innovative approaches to using challenging data-are well positioned to contribute to this area of work. We discuss the benefits and challenges of using digital trace data for social and demographic research, and we review examples of current demographic literature that creatively use digital trace data to study processes related to fertility, mortality, and migration. Focusing on Facebook data for advertisers-a novel "digital census" that has largely been untapped by demographers-we provide illustrative and empirical examples of how demographic researchers can manage issues such as bias and representation when using digital trace data. We conclude by offering our perspective on the road ahead regarding demography and its role in the data revolution. [ABSTRACT FROM AUTHOR]

Information communications technologies (ICTs) like laptops, smartphones and portable storage devices facilitate travel, communication and documentation for researchers who conduct fieldwork. But despite increasing awareness about the ethical complications associated with using ICTs among journalists and humanitarians, there are few reflections on digital security among researchers. This article seeks to raise awareness of this important question by outlining three sets of ethical challenges related to digital security that may arise during the course of field research. These ethical challenges relate to (i) informed consent and confidentiality, (ii) collecting, transferring and storing sensitive data, and (iii) maintaining the personal security and integrity of the researcher. To help academics reflect on and mitigate these risks, the article underscores the importance of digital risk assessments and develops ten basic guidelines for field research in the digital age. [ABSTRACT FROM AUTHOR]

Geberth in 2006 stated that "staging is a conscious criminal action on the part of an offender to thwart an investigation." In the present paper two crime scenes staged by handling digital evidence are reported. The first case involves a 50-year-old woman who had been living with the offender for three years before he murdered her at the end of their relationship. He staged the scene as a sex-related crime committed by an unknown perpetrator. The second case concerns a young woman who was found dead in Southern Italy in January 2004 with a gunshot on the forehead. The boyfriend, responsible for the murder, had staged the crime scene as a suicide. Three years earlier in Germany, he had also murdered the victim's mother. In both cases, the correlation of physical and digital forensic evidence was crucial in the definition of the manner of death. [ABSTRACT FROM AUTHOR]

The first two decades of the twenty-first century have seen a rapid rise in the mobilization of digital biodiversity data. This has thrust natural history museums into the forefront of biodiversity research, underscoring their central role in the modern scientific enterprise. The advent of mobilization initiatives such as the United States National Science Foundation's Advancing Digitization of Biodiversity Collections (ADBC), Australia's Atlas of Living Australia (ALA), Mexico's National Commission for the Knowledge and Use of Biodiversity (CONABIO), Brazil's Centro de Referência em Informação (CRIA) and China's National Specimen Information Infrastructure (NSII) has led to a rapid rise in data aggregators and an exponential increase in digital data for scientific research and arguably provide the best evidence of where species live. The international Global Biodiversity Information Facility (GBIF) now serves about 131 million museum specimen records, and Integrated Digitized Biocollections (iDigBio) in the USA has amassed more than 115 million. These resources expose collections to a wider audience of researchers, provide the best biodiversity data in the modern era outside of nature itself and ensure the primacy of specimen-based research. Here, we provide a brief history of worldwide data mobilization, their impact on biodiversity research, challenges for ensuring data quality, their contribution to scientific publications and evidence of the rising profiles of natural history collections. [ABSTRACT FROM AUTHOR]