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The AUD2IT-algorithm is a tool to structure the data, which is collected during an emergency treatment. The goal is on the one hand to structure the documentation of the data and on the other hand to give a standardised data structure for the report during handover of an emergency patient. AUD2IT-algorithm was developed to provide residents a documentation aid, which helps to structure the medical reports without getting lost in unimportant details or forgetting important information. The sequence of anamnesis, clinical examination, considering a differential diagnosis, technical diagnostics, interpretation and therapy is rather an academic classification than a description of the real workflow. In a real setting, most of these steps take place simultaneously. Therefore, the application of the AUD2IT-algorithm should also be carried out according to the real processes. A big advantage of the AUD2IT-algorithm is that it can be used as a structure for the entire treatment process and also is entirely usable as a handover protocol within this process to make sure, that the existing state of knowledge is ensured at each point of a team-timeout. PR-E-(AUD2IT)-algorithm makes it possible to document a treatment process that, in principle, does not have to be limited to the field of emergency medicine. Also, in the outpatient treatment the PR-E-(AUD2IT)-algorithm could be used and further developed. One example could be the preparation and allocation of needed resources at the general practitioner. The algorithm is a standardised tool that can be used by healthcare professionals of any level of training. It gives the user a sense of security in their daily work.

High Speed 2 (HS2) will be the largest programme of historic environment investigation and recording works ever undertaken in the UK. It is certain that the creation of HS2's historic environment physical and digital archive (High Speed Two Ltd. 2023) is an integral part of the lasting legacy of the programme, which presents an unprecedented opportunity for significant knowledge creation. HS2 historic environment works that have been undertaken for Phase One of HS2 between London to the West Midlands has resulted in a substantial digital archive, including Geographic Information Systems (GIS) data. This data paper highlights the GIS spatial datasets generated from the HS2 Phase One historic environment fieldwork programme. It explains the technical components of the datasets which are deposited with the Archaeology Data Service (ADS).

For the interval 1962-2022 y, during the continuos publication last 60 years, in Metalurgija Journal Authors from 40 countries from Mexico to China (all 5 continent ) have publish. The goal of the Article is give List of Papers published in this interval, 199 issues or 238 numbers, 2721 scientific and technical, and 287 contributions (total 3008 papers ) of Authors whose investigation results and ideas have been examined and found on the pages of this Journal. Thanks for all.

The interaction of wood and moisture has to be considered in many industrial sectors. Wood is highly hygroscopic material while the absorbed moisture affects all its technical properties. One of them is a moisture permeability which is further affected by the sorption hysteresis and also differs in the three wood anatomical directions – radial, tangential, and axial. For the prediction of the dynamic hygro-thermal behaviour of wood can be used numerical simulation tools. However, data from carefully designed and controlled experiments are needed for reliable validation of these tools. This paper presents data from a 45-day dynamic laboratory experiment. The one-dimensional moisture transport in spruce wood in the tangential and radial directions under isothermal conditions was studied. The samples were exposed to cyclic step-changes in relative humidity 72–95 % at 23 °C. Data show the rate of stabilisation of moisture content in the samples, the effect of sorption hysteresis, and changes in the temperature of samples due to moisture sorption. In addition, the paper also presents material functions describing the sorption properties and moisture permeability of spruce wood. These properties were determined based on laboratory measurements using the spruce wood of the same origin as used for the dynamic experiment. The dynamic data, together with the proposed material functions can be used in the development or verification of hygro-thermal numerical simulation tools.

This paper will discuss Data, Information, Knowledge, and Wisdom, which is commonly referred to as DIKW. The DIKW Pyramid Model is a hierarchical model that is often referenced in both academic and practitioner circles. This model will be discussed and shown to be faulty on several levels, including a lack of definitional agreement. A new DIKW framework with systems orientation will be proposed that focuses on what the DIKW elements do in the way humans think, not what they are by definition. Information as a replacement for wasted physical resources in goal-oriented tasks will be a central organizing point. The paper will move the DIKW discussion to the computer-based concept of Digital Twins (DTs) and its augmentation of how we can use DIKW to be more effective and efficient. This will especially be the case as we move toward Intelligent Digital Twins (IDTs) with Artificial Intelligence (AI).

Abstract Through an ethnographic study of Chinese IT professionals who integrate a form of data culture into the digital platforms they design, maintain, and operate daily within one of China’s tech giants, this paper reveals numerous overlaps and interrelations between the data practices of Chinese IT professionals and the broader social implications that arise from them. The aim is to foster a more productive dialogue between the social studies of quantification and platform studies. This original research proposes the backstage as a potent methodology for inquiring into the role of Chinese IT professionals and domestic tech giants in advancing measuring systems and audit culture. This paper concludes by suggesting that such an approach can also be applied to wider studies of the paradox in quantification between its general claims and specific effects.

(Series Information) European Papers - A Journal on Law and Integration, 2023 8(2), 405-410 | European Forum Highlight of 26 July 2023 | (Abstract) The Digital Markets Act (DMA) intends to ensure contestable and fair markets in the digital sector through the introduction of obligations for “gatekeepers”. This term represents a legal innovation. No mention of gatekeepers can be retrieved in the case law regarding digital platforms, and the origins of the nomenclature cannot be ascribed to competition law. The concept can, however, be linked to information studies: its adoption in the DMA reflects the centrality of information control for contestability and fairness. A look at the DMA treatment of gatekeepers reveals that, on the one hand, it is coherent with an information-based approach, while on the other it is not devoid of elements typical of a competition law approach. Only the future interpretation of the DMA will show whether the Regulation is an attempt to inform competition policy with notions fit for the data economy or if it is bound to depart from a competition-based reading.

Software engineering is an empirical field of study. To support managerial and technical decision-making, the engineer needs numerical measures closely connected with different software metrics. Visual representation of numerical data improves the effectiveness of human data processing and shows insights that humans may miss. This paper aims to provide a systematic review of the approaches for software metrics visualization and define the possible recommendation for their use. The study is based on the literature review of the papers from two text collections – IEEE Xplore and ACM Digital Library – and the scientometric database Scopus. After merging and filtering, the final set of publications contains 16 papers. Our study showed that there were the metrics used significantly more often; among them are lines-of-code, cyclomatic complexity, coupling, and cohesion. We were not able to identify such leaders for visualization means. Instead, there was a tendency to combine different metrics on one chart or dashboard to provide the whole process picture. Based on the results of empirical studies reported in the literature, we offered an analysis of simple charts’ properties and recommendations on their use for support decision-making in the software engineering process.

Artificial intelligence (AI) systems are trained to solve complex problems and learn to perform specific tasks by using large volumes of data, such as prediction, classification, recognition, decision-making, etc. In the past three decades, AI research has focused mostly on the model-centric approach compared to the data-centric approach. In the model-centric approach, the focus is to improve the code or model architecture to enhance performance, whereas in data-centric AI, the focus is to improve the dataset to enhance performance. Data is food for AI. As a result, there has been a recent push in the AI community toward data-centric AI from model-centric AI. This paper provides a comprehensive and critical analysis of the current state of research in data-centric AI, presenting insights into the latest developments in this rapidly evolving field. By emphasizing the importance of data in AI, the paper identifies the key challenges and opportunities that must be addressed to improve the effectiveness of AI systems. Finally, this paper gives some recommendations for research opportunities in data-centric AI.

Unmanned Aerial Vehicles (UAVs), or drones, have rapidly transformed from niche gadgets to versatile tools with widespread applications across various sectors. This paper investigates the regulatory landscape of drones within the European Union (EU) and its intricate balance between fostering technological innovation and addressing safety, privacy, security, and environmental concerns. Drones’ exponential growth in Europe’s airspace has prompted the EU to establish a legal framework that addresses their multifaceted implications. While drones offer unprecedented opportunities in areas like disaster response and remote sensing, they also pose challenges such as airspace congestion, potential privacy breaches, and ecological disturbances. This paper examines the evolving legal frameworks, policy developments, and technological advancements that characterize drone regulation in the EU. The study delves into key considerations including air traffic management, data protection, privacy preservation, environmental sustainability, and international collaboration. By analysing EU regulations, such as the European Aviation Safety Agency (EASA) standards, the General Data Protection Regulation (GDPR), and European initiatives on unmanned aircraft systems, this paper uncovers the complex interplay of legal, technical, and ethical dimensions.

(Series Information) European Papers - A Journal on Law and Integration, 2022 7(3), 981-992 | European Forum Insight of 23 December 2022 | (Table of Contents) I. A competition policy fit for the digital transition? The Commission's view. - II. The complementary role of competition law: a dynamic balance between rules and exceptions. - III. The degree of (de)centralisation of public enforcement to ensure the dynamic balance. - IV. Final considerations. | (Abstract) The European responses to the COVID-19 outbreak have triggered an ongoing review process of competition rules and enforcement procedure to support the Union's priorities. In this context, the European Commission published the Communication 'A Competition Policy Fit for New Challenges' with the aim of underlining the ability of competition law to facilitate the green and digital transitions, and to strengthen the resilience of the Single Market. This Insight reflects on the substantive and procedural challenges posed by the digital transition. Indeed, the complementary role of competition law to stimulate the achievement of the digital targets is characterised by two tensions, relating respectively to the interpretation and application of competition rules and to the degree of centralisation with regard to the enforcement mechanisms. In the author's view, EU competition law will offer dynamic substantive and procedural responses to the challenges of the digital transition.

The last 30 years have seen significant investments in the development of digital infrastructures to support archaeological practice. From field recording systems to national data archives, these have come to play an increasingly dominant role in the collection, management, and access to the data used in the creation of new archaeological knowledge. Although a lot of attention has been paid to the technical creation of such systems, much less is said about the wider political, cultural and social aspects of these infrastructures. Focusing on large-scale national or transnational data infrastructures, this paper seeks to lay the groundwork for such an inquiry by making the infrastructure the centre of analysis, rather than its technical aspects. The paper asks how infrastructures emerge, are sustained, become embedded in practice, and how they subsequently contextualise and influence the formation of archaeological knowledge. The underlying and frequently hidden complexities of infrastructures and their nature as always under development should make a critical understanding of their implementation and application, the opportunities they offer, the constraints they impose, and the perspectives they adopt, an important precursor to their knowledgeable use in practice.

Large-scale projects, such as infrastructure or long-term research, generate some of the largest data sets which form the core of their legacy for research and future projects. Due to the scale of the data being generated and managed, projects have developed innovative approaches to transform data into meaningful information and ensure integration of data into the project lifecycle. This paper serves to present the background and context for the session presented at EAA 2022, Budapest, organised by HS2 Ltd and Jacobs Suedlink and summarises some of the papers presented within the session and which are now published in this issue.

Web 4.0 revolution and the abundance of industrial data in the current business environment allow each industrial company to innovate in a diversity of ways. The novelty approaches for the industry are often related to Industry 4.0, where data plays a key role. This research paper aims to develop a new model of the Sub-Supplier process description „Sub-Suppliers Model 4.0“. The model presents the role of knowledge management and Web 4.0 as having a key impact on the processes for business value creation for the industrial organisation. The paper is structured into three chapters. The introduction presents the methods used along with the research question. Chapter one starts with the theoretical bases and state of the art of the Industrial Sub-Supplier Process (ISSP). Chapter two makes a link between the ISSP, knowledge management and knowledge discovery process using data from Supply Chain Management Software for management decision-making. Chapter three of the research starts with web 4.0 tools and proposes a Sub-Suppliers Model 4.0, while trying to explain how the ISSP can be optimized based on the KPIs used. The main research contribution is the novelty integration of the knowledge discovery concept and the implementation of web 4.0 tools into the ISSP.

This paper is devoted to the transport of slaughter animals. There are obstacles that needs to be pointed out, removed, and resolved. General requirements for the movement of slaughter animals within the Union have proven to be an unjustified administrative burden and costly. It also presents how important is to keep and follow all the rules provided by European Union to prevent any issues and keep the animals in good conditions and welfare during the transport. Bad conditions and not keeping the rules during animal transport can cause the stress of the animals and have a huge effect on their health. The stress can cause injuries and even a death of the animals that were healthy and had no signs of any sickness before the transfer. The main goal of the paper is to present the circumstances under which safe transport depends on choosing the correct logistical management, starting with the proper vehicles. Specific rules apply depending on the type and quantity of animals transported. The paper explains and summarizes the special establishment for road transport, including all mandatory actions, documents, and data centralisation (COMEX, TRACES, IMSOC).

Introduction/purpose: Reliability and availability are important especially for military, medical, and other professional equipment. Reliability and availability management and/or prognostic reliability calculations have always been data driven. This article focuses on the analysis of the data impact on reliability and availability. Methods: This research is based mostly on the articles published by the author of this work as well as on some other papers. Results: This paper results in a discussion on the definition of the datadriven concept, preceded by brief definitions of reliability and availability, and followed by the analysis of the main impacts of uncertain data on prognostic reliability calculations as well as by reliability and availability of data used in reliability calculations. Conclusions: Reliability and availability are still very important. Reliability and availability have always been data driven while valid and relevant data have always been the main problem. Without good data, prognostic reliability is useless in spite of a good reliability model.

Transactions on Graph Data and Knowledge (TGDK) is a new journal publishing peer-reviewed research on graph-based abstractions for data and knowledge, as well as the techniques, theories, applications and results that arise in this setting. TGDK is a community-run, Diamond Open Access journal, meaning that papers are published openly on the Web without fees for authors or readers. In this preface, we provide some brief remarks about the rationale and goals of the new journal, followed by an introduction to its inaugural issue, entitled "Trends in Graph Data and Knowledge", which collects together 12 diverse vision, position and survey papers on the types of research topics that exemplify the scope of this new journal.

Social simulation studies are complex. They typically combine various data sources and hypotheses about the system’s mechanisms that are integrated by intertwined processes of model building, simulation experiment execution and analysis. Various documentation approaches exist to increase the transparency and traceability of complex social simulation studies. Provenance standards enable the formalization of information on sources and activities, which contribute to the generation of an entity, in a queryable and computationally accessible manner. Provenance patterns can be defined as constraints on the relationships between specific types of activities and entities of a simulation study. In this paper, we refine the provenance pattern-based approach to address specific challenges of social agent-based simulation studies. Specifically, we focus on the activities and entities involved in collecting and analysing primary data about human decisions, and the collection and quality assessment of secondary data. We illustrate the potential of this approach by applying it to central activities and results of an agent-based simulation project and by presenting its implementation in a web-based tool.

Energy systems modelling plays a pivotal role in understanding and optimizing complex energy systems. By integrating various factors such as energy demand, supply, infrastructure, and environmental considerations, energy systems modelling provides valuable insights for policymakers, industry stakeholders, and researchers. This can be key to informing stakeholder and policy decisions and facilitate the mobilisation of capital and market development to support the development of the energy sector. This article presents the data, assumptions, and related calculations used for the development of a national scale power system model for Sierra Leone. The focus of the model was a techno-economic analysis of specific hydropower expansion plans. Where possible, this data has been collected from publicly available sources such as scientific literature, feasibility studies, international databases, data from existing modelling efforts in Sierra Leone, and local stakeholders. The collection of the data, development of the model, and creation of scenarios was done in collaboration with the Ministry of Energy in Sierra Leone and verified by a broad range of stakeholders.The following paper outlines the key data presented in the full database which can be accessed through the link found in the Specifications Table. The link also contains the Reference Energy System (RES) used in this study.

This paper presents a comprehensive dataset on the global trade dynamics of COVID-19-related medical products for the years 2019 and 2020. The dataset, derived from the BACI database, focuses on eight distinct product categories identified by six-digit codes. The trade flow data for 224 countries is structured as a multilevel network, with countries as nodes and product categories as layers. Directed edges represent trading activities, and edge weights are determined by the difference in exported values between 2019 and 2020. The dataset is provided in an edges-and-nodes format. Additionally, the associated R script transforms the data into the MuxViz R package format, facilitating further analysis and visualization of the dataset. The dataset is valuable for researchers in the field of foreign trade or medical products, and for decision-makers in these fields, whether at company or national level.

In the ongoing academic discussion regarding what happens to our data after we die, how our data are utilised for commercial profit-making purposes, and what kinds of death-related practices our posthumous data figure in, the notion of digital afterlife is attracting increasing attention. While the concept of digital afterlife has been approached in different ways, the main focus remains on the level of individual loss. The emphasis tends to be on the role of posthumous digital artefacts in grief practices and death-related rituals or on data management issues relating to death. Building on a socio-technical view of digital afterlife, this paper offers, as a novel contribution, an understanding of digital afterlife as a techno-affective assemblage. It argues for the necessity of examining technological and social factors as mutually shaping and brings into the discussion of digital afterlife the notions of relationality, materiality, and the affective potential of data. The paper ends with ruminations about digital afterlife as a posthumanist project.

This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

Apache Kafka has become a popular solution for managing networked data streaming in a variety of applications, from industrial to general purpose. This paper systematically surveys the research literature in this field by carefully classifying it into key macro areas, namely algorithms, networks, data, cyber-physical systems, and security. Through this meticulous classification, the paper aims to identify and analyze the optimization aspects relevant to each area, drawing upon practical applications as the basis for analysis. In this respect, the paper synthesizes and consolidates existing knowledge, saving researchers valuable time and effort in searching for relevant information across multiple sources. The tangible benefits of this survey paper include providing a consolidated knowledge base about research-intensive Apache Kafka topics, highlighting practical insights and novel approaches, pointing up cross-domain applications, identifying related research challenges, and serving as a trusted reference for the Apache Kafka community.

Digital objects are now pervasively used across the heritage sciences, often as 3D models. However, the theoretical discussion of what these objects are, ontologically speaking, can be diverse, ranging, and inconclusive. This paper will focus on the Cherish Project, a European research initiative that used a range of methods—including drone-based photogrammetry and laser scanning— to create 3D models of coastal heritage landscapes that are at risk due to climate change. In specifically attending to the database storage schemes and software/platforms employed by Cherish, this paper explores how digital heritage objects can more broadly be discussed in terms of their ontological multiplicity, the multi-sitedness of their production and circulation, and their mobility across interfaces as they are formalised and circulated. In tracing these specific factors, this paper arrives at epistemological insights about how digital heritage objects factor into knowledge producing practices like Cherish, foregrounding critical questions about how these practices might be differently discussed, pursued, or imagined.

The sustainable development of cities relies on the implementation of multi-sectoral actions towards carbon neutrality, reducing the air pollutants emissions. The actions' decision-making process for cities transformation should be supported by lessons learnt from previous interventions and KPIs (Key Performance Indicators). To do so, gathering real data becomes pivotal, complementing simulation tools (currently used), solving the inherent uncertainties due to assumptions. Data collection methodologies are then necessary, being the main driver for digital cities and providing better mechanisms for informed decision-making. Most of the cities still operate in silos and do not always implement the strategic plans supported with a digitalization of the municipal processes. Within this perspective, this paper presents a methodology to support cities in the preparation of monitoring programmes to collect real data in a robust and feasible manner. Taking the KPIs and the Smart Cities urban strategies into account, this paper concludes with some lessons learnt within cities to deploy monitoring approaches. From the city challenges to the review of the plans, all the process is driven by real data and KPIs. The methodology has been applied in the mySMARTLife project (Grant Agreement #731297) and deployed into the cities of Nantes (France), Hamburg (Germany) and Helsinki (Finland).

The study of platforms, or multi-sided markets, has seen exponential growth in economics, media studies, social sciences and humanities. However, the critical political economy of media has been relatively quiet, with notable exceptions in areas such as platform capitalism, imperialism and especially platform labour and gig work. However, traditional Marxian production, often taken as the starting point, relies on the labour theory of value and struggles to capture all platform specificities. Due to their integrated understanding of production and circulation of value, I will argue that New Readings of Marx and Open Marxism help study platforms as linchpins of internet user lifeworlds and the global economy. In this literature, capitalism is analysed as a historically specific social form of production. Additionally, these approaches can address some theoretical problems that occasionally occur with related Marxian theories, such as unpaid digital labour, rent, and techno-feudalism. In that sense, this paper aims to contribute to the critical political economy of the media and the study of platforms by bringing previously neglected theoretical approaches to the centre stage and unpacking platforms as social forms of production and circulation in contemporary capitalism.

The original vision on what later became LifeWatch ERIC started about a quarter of a century ago in 1996. In those days, the promise of digital technologies entered biodiversity and ecosystem research. Not only by digitiing relevant information, but also with applications to process such data. While several (inter)national initiatives embarked on specific topics, there was also an idea that the upcoming view on grid computing provided attractive solutions for federated data sources, together with a strong computing capacity. This paper presents the history from conception to early actions, until actual preparations towards a research infrastructure on the European scale.

BackgroundEffective management of the COVID-19 pandemic required rapid expansion of diagnosis. The introduction of antigen tests presented an opportunity to decentralize testing, but raised challenges with ensuring accurate and timely reporting of testing data, which is essential to guide the response. Digital solutions can help address this challenge and provide more efficient means of monitoring and quality assurance.MethodsUganda’s existing laboratory investigation form was digitized in the form of an Android-based application, eLIF, which was developed by the Central Public Health Laboratory and implemented in 11 high-volume facilities between December 2021 and May 2022. The app enabled healthcare workers to report testing data via mobile phone or tablet. Uptake of the tool was monitored through a dashboard that enabled real-time visibility into data being transmitted from sites, as well as qualitative insights from site visits and online questionnaires.Results and discussionA total of 15,351 tests were conducted at the 11 health facilities during the study period. Of these, 65% were reported through eLIF, while 12% were reported through preexisting Excel-based tools. However, 23% of tests were only captured in paper registers and not transmitted to the national database, illustrating the need for increased uptake of digital tools to ensure real-time data reporting. While data captured through eLIF were transmitted to the national database within 0–3 days (min, max), data transmitted through Excel were transmitted in within 0–37 days (min, max), and data for paper-based reporting took up to 3 months. The majority of healthcare workers interviewed in an endpoint questionnaire responded that eLIF improved timeliness of patient management, and reduced reporting time. However, some functions of the app were not successfully implemented, such as providing random selections of samples for external quality assurance and enabling seamless linkage of these data. Challenges arose from broader operational complexities, such as staff workload, frequent task-shifting and unexpected changes to facility workflows, which limited adherence to the envisioned study procedures. Ongoing improvements are needed to adjust to these realities, to strengthen the technology and support to healthcare workers using it, to optimize the impact of this digital intervention.

Mobility-as-a-Service (MaaS) is regarded as key innovation for sustainable mobility, with data and AI playing a central role. This paper explores the nexus of data-AI-governance in MaaS to understand in how far sustainability is addressed. While the role of data and AI is covered by technical literature, and governance by social science literature, these discussions remain largely separate in MaaS. This paper aims to redress this issue through an interdisciplinary narrative literature review that brings together these literature sets. The research question is: How does the data-AI-governance nexus in MaaS give rise to hybrid forms of governance between humans and algorithms and what are the implications for sustainable mobility? Results show that: (1) The data collection and processing that is crucial to MaaS, might reproduce socio-political inequalities. (2) AI-driven customisation and nudging of end-user demand ignores rebound effects, that can only be avoided if sustainability objectives are central. (3) Inadequate integration of mobility service supply might exacerbate mobility challenges. (4) When mobility system optimisation through AI becomes more widespread, MaaS platforms might become a form of algorithmic governance. (5) Whether sustainability can be reached, depends on how and by whom (sustainability) objectives of algorithms will be decided. The paper concludes that hybrid governance for sustainability requires close collaboration between policymakers and industry players and acknowledging AI algorithms as important non-human actors. The paper contributes to conceptual debates on sustainability and data/AI, governance and data/AI in MaaS and beyond, and to policymaking on aligning platform systems with sustainability.

Urbanization and climate change have increased the need for stormwater management and nature-based solutions. Decisions made at the project level impact the emergence of the systemic traits of the stormwater network and the functionality of the catchment areas in urban planning. To that end, it is vital to introduce the decision-making tools for analysing both the utilities and amenities of nature-based solutions (NBS) to increase their adoption to reduce the peak loads in the stormwater system and, to that end, mitigate the impacts of climate change. There is a deficiency in employing a software-based approach to analyse the qualitative and quantitative aspects of NBSs to back up design decisions. This paper demonstrates a workflow using drone-based photogrammetry, 3D modelling, and simulation software to generate visual and functional models assisting in informed decision-making in the design of stormwater systems as functional landscape architecture. Using aerial data from drones and modelled design solutions, the proposed workflow simulates rain events, infiltration, evaporation, water flow, and the accumulation of stormwater in a way that allows the visual and quantified analysis of detailed landscape architecture designs. The paper provides an example of a rooftop site simulation demonstrating the infiltration and flow of water to the drainage. The visual decision-making method provided can aid in investment decisions for functional landscape design in support of stormwater management.

There is an increasing desire to study neurodevelopmental disorders (NDDs) together to understand commonalities to develop generic health promotion strategies and improve clinical treatment. Common data elements (CDEs) collected across studies involving children with NDDs afford an opportunity to answer clinically meaningful questions. We undertook a retrospective, secondary analysis of data pertaining to sleep in children with different NDDs collected through various research studies. The objective of this paper is to share lessons learned for data management, collation, and harmonization from a sleep study in children within and across NDDs from large, collaborative research networks in the Ontario Brain Institute (OBI). Three collaborative research networks contributed demographic data and data pertaining to sleep, internalizing symptoms, health-related quality of life, and severity of disorder for children with six different NDDs: autism spectrum disorder; attention deficit/hyperactivity disorder; obsessive compulsive disorder; intellectual disability; cerebral palsy; and epilepsy. Procedures for data harmonization, derivations, and merging were shared and examples pertaining to severity of disorder and sleep disturbances were described in detail. Important lessons emerged from data harmonizing procedures: prioritizing the collection of CDEs to ensure data completeness; ensuring unprocessed data are uploaded for harmonization in order to facilitate timely analytic procedures; the value of maintaining variable naming that is consistent with data dictionaries at time of project validation; and the value of regular meetings with the research networks to discuss and overcome challenges with data harmonization. Buy-in from all research networks involved at study inception and oversight from a centralized infrastructure (OBI) identified the importance of collaboration to collect CDEs and facilitate data harmonization to improve outcomes for children with NDDs.

In the evolving landscape of mixed human-machine driving environments, autonomous vehicles (AVs) confront the challenge of anticipating the lane-changing intentions and subsequent driving trajectories of neighboring vehicles. This capability is essential for optimizing safety, efficiency, and comfort in decision-making processes. This paper introduces a novel hybrid prediction model, the LSTM-GAT-Bilayer-GRU, which leverages deep learning to enhance predictive accuracy and real-time responsiveness in dynamic traffic scenarios. The proposed model consists of two main components: a lane change prediction model (LSTM-GAT) and a trajectory prediction model (G-BiLayer-GRU), to process and predict complex vehicular interactions and environmental dynamics effectively. The efficacy of this integrated model was tested using the HighD dataset for training, validation, and testing purposes. The results of a benchmark analysis indicate that the proposed model demonstrated superior prediction performance and reliability over the Support Vector Machine (SVM), Random Forest (RF), AlexNet and Back-Propagation Through Time (BPTT) in the context of lane change intention recognition. Combining LSTM for temporal data processing with GAT for spatial interaction analysis, along with the GRU’s precise trajectory prediction, achieved the best error evaluation metric and balanced prediction time consuming metric under the six prediction time-interval, marks a substantial advancement in AVs technology. This integration guarantees smooth operation of AVs in intricate driving scenarios, fine-tuning their reactions to bolster road safety and passenger comfort.

This paper describes the possibility of applying heuristic methods for parameter optimization in the TCP protocol. The proposed concept provides for a TCP protocol adjusting its parameters for greater efficiency through testing the network state and adapting accordingly. This can be achieved through careful analysis of the network state both before and during data transfer connections. The proposed solution introduces an innovative approach, incorporating the possibility of self-learning and self-adjusting capabilities. This sophisticated algorithm should define the next parameter values in terms of finding optimal parameter settings. Each TCP connection plays a crucial role as iteration in the process of finding the optimal solution. The concept focuses on calculating TCP parameter values at the network ends in order to optimize network traffic and to maximize the use of network resources. The approach has been tested on a dedicated test platform, validating its potential for verifying the network protocols functionality and for optimizing their parameters. The proposed solution, here referred to as the modified TCP, showed better performance compared to other versions of the TCP protocol. Notably, even under heavy traffic loads on links, the results for the modified TCP consistently outperform the standard TCP, delivering results that are several times better.

Major countries around the world are leveraging information and communications technology (ICT), such as artificial intelligence, big data, cloud computing and cybersecurity, to strengthen their militaries. These technological advancements are driving the changes in weapon systems, strategies, and tactics. In 2021, the South Korean Ministry of National Defense introduced the concept of “military meta power” to describe the power generated in the cognitive military domain utilizing ICT. This concept is significant in that it differentiates between cognitive and physical military power, emphasizing the importance of the cognition-based power in future warfare. Additionally, the concept consolidates various cognitive military capabilities, including AI capability, cyber capability, space capability, and C4ISR (Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance), into a unified ICT-generated power. This study aims to contribute to the literature on “military meta power” by providing a comprehensive overview of its characteristics, composition, and attributes. To achieve this objective, the research begins with an exploration of the philosophical insights on technology related to ICT, followed by a comprehensive review of the perspectives of existing academic papers. Finally, this study provides an in-depth analysis of various military strategies.

Abstract Background This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS). Methods A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs. Results We provide an overview of NILS RSU infrastructure design changes that have been implemented to date, focusing on a website redesign to meet user information requirements and the formation of better working partnerships between data users and providers within the Northern Ireland data landscape. We also discuss the key challenges faced by the design team during this project of transformation. Conclusion Our primary objective to improve government data infrastructure and to increase dissemination and the impact of research based on data was a complex and multifaceted challenge due to the number of stakeholders involved and their often conflicting perspectives. Results from this CI approach have been pivotal in highlighting how NILS RSU can work collaboratively with users to maximize the potential of this data, in terms of forming multidisciplinary networks to ensure the research is utilized in policy and in the literature and providing academic support and resources to attract new researchers.

Ayogeboh Epizitone,1 Smangele Pretty Moyane,2 Israel Edem Agbehadji3 1ICT and Society Research Group, Department of Information and Corporate Management, Durban University of Technology, Durban, South Africa; 2Department of Information and Corporate Management, Durban University of Technology, Durban, South Africa; 3Centre for Transformative Agricultural and Food Systems, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South AfricaCorrespondence: Ayogeboh Epizitone, Tel +27 73-310-9150, Email ayogebohe@dut.ac.zaIntroduction: Many transformations and uncertainties, such as the fourth industrial revolution and pandemics, have propelled healthcare acceptance and deployment of health information systems (HIS). External and internal determinants aligning with the global course influence their deployments. At the epic is digitalization, which generates endless data that has permeated healthcare. The continuous proliferation of complex and dynamic healthcare data is the digitalization frontier in healthcare that necessitates attention.Objective: This study explores the existing body of information on HIS for healthcare through the data lens to present a data-driven paradigm for healthcare augmentation paramount to attaining a sustainable and resilient HIS.Method: Preferred Reporting Items for Systematic Reviews and Meta-Analyses: PRISMA-compliant in-depth literature review was conducted systematically to synthesize and analyze the literature content to ascertain the value disposition of HIS data in healthcare delivery.Results: This study details the aspects of a data-driven paradigm for robust and sustainable HIS for health care applications. Data source, data action and decisions, data sciences techniques, serialization of data sciences techniques in the HIS, and data insight implementation and application are data-driven features expounded. These are essential data-driven paradigm building blocks that need iteration to succeed.Discussions: Existing literature considers insurgent data in healthcare challenging, disruptive, and potentially revolutionary. This view echoes the current healthcare quandary of good and bad data availability. Thus, data-driven insights are essential for building a resilient and sustainable HIS. People, technology, and tasks dominated prior HIS frameworks, with few data-centric facets. Improving healthcare and the HIS requires identifying and integrating crucial data elements.Conclusion: The paper presented a data-driven paradigm for a resilient and sustainable HIS. The findings show that data-driven track and components are essential to improve healthcare using data analytics insights. It provides an integrated footing for data analytics to support and effectively assist health care delivery.Keywords: health information system, HIS, data, healthcare, analytics

The EU and other states have made legislative efforts to clarify data mining in copyrightable works, but the situation remains obscure and confusing, especially in a globalised field where international legislation can contribute to opacity. The present paper aims at asserting a common position of three communities representing biodiversity sciences and data specialists on this issue and to propose common and best practice guidelines so that they become universally accepted rules.As scientific data users, we take the standpoint that scientific data are not copyrightable and, furthermore, they can be accessed, shared and reused freely. Thus, once legal access has been gained to copyrighted publications, the data within those scholarly publications can be considered to be open data that is freely extractable. This set of recommendations has been reached specifically for scientific use and societal benefits.

The sensitivity and exclusivity attached to personal health records make such records a prime target for cyber intruders, as unauthorized access causes unfathomable repudiation and public defamation. In reality, most medical records are micro-managed by different healthcare providers, exposing them to various security issues, especially unauthorized third-party access. Over time, substantial progress has been made in preventing unauthorized access to this critical and highly classified information. This review investigated the mainstream security challenges associated with the transmissibility of medical records, the evolutionary security strategies for maintaining confidentiality, and the existential enablers of trustworthy and transparent authorization and authentication before data transmission can be carried out. The review adopted the PRSIMA-SPIDER methodology for a systematic review of 122 articles, comprising 9 surveys (7.37%) for qualitative analysis, 109 technical papers (89.34%), and 4 online reports (3.27%) for quantitative studies. The review outcome indicates that the sensitivity and confidentiality of a highly classified document, such as a medical record, demand unabridged authorization by the owner, unquestionable preservation by the host, untainted transparency in transmission, unbiased traceability, and ubiquitous security, which blockchain technology guarantees, although at the infancy stage. Therefore, developing blockchain-assisted frameworks for digital medical record preservation and addressing inherent technological hitches in blockchain will further accelerate transparent and trustworthy preservation, user authorization, and authentication of medical records before they are transmitted by the host for third-party access.

Monitoring microclimate variables within cities with high resolution and accuracy is crucial for enhancing urban resilience to climate change. Assessing intra-urban characteristics is essential for ensuring satisfactory living standards. This paper presents a comprehensive methodology for studying urban heat islands (UHIs) on a university campus, emphasizing the importance of multi-modal and multi-temporal data collection. The methodology integrates mobile surveys, stationary sensor networks, and drone-based thermal imaging, providing a detailed analysis of temperature variations within urban microenvironments. The preliminary findings confirm the presence of a UHI on the campus and identify several hotspots. This comprehensive approach enhances the accuracy and reliability of UHI assessments, offering a cost-effective, fine-resolution approach that facilitates more effective urban planning and heat mitigation strategies.

Information is the new commodity in the global economy and trustworthy digital repositories will be the key pillars within this new ecosystem. The value of this digital information will only be realised if these repositories can be interacted with in a consistent manner and their data accessible and understandable globally. Establishing a data interoperability layer is the goal of the emerging domain of Digital Objects. When considering how to proceed with designing this interoperability layer, it is important to state that repositories need to be considered from two different perspectives:Repositories are a reflection of the institutions that make them operational (quality of service, skilled experts, accessible over many years, appropriate data management procedures).Repositories are computational services that provide a specific set of functions.Complicating the effort to make repositories accessible and interoperable across the global is that many existing repositories have been developed in the past decades using a wide range of heterogeneous technologies, organisation of data and functionality. Many of these repositories are their own data silos and not interoperable. It is important to realise that much money has been invested to build these repositories and therefore we cannot expect that they will make large changes without great incentives and funding. This heterogeneity is the core of the challenge in making digital information the new commodity in the emerging global domain of digital objects.This paper will focus on the functional aspects of repositories and proposes the FAIR Digital Object model as a core data model for describing digital information and the use of the Digital Object Interface Protocol (DOIP) to establish interoperable communication with all repositories independently of the respective technical choices. It is the conviction of this paper’s authors that this integration of the FDO model and DOIP with existing repositories can be performed with minimal effort and we will present examples that document this claim.We will present three examples of existing integration in this paper:An integration of B2SHAREA CORDRA repositoryIntegration of the DOBES archiveB2SHARE is a repository that has assigned Persistent Identifiers (PIDs) (Handles) to all of its digital files. It allows users to add metadata according to a unified schema, but also has the possibility for user communities to extend this schema. The API allows one to specify a Handle which then gives access to the metadata and/or the bit sequences of the DO. It should be noted that B2SHARE allows one to include a set of bit-sequences being linked with the Handle. The integration consists of building a proxy that would provide a DOIP interface to B2SHARE to streamline the integration of the data and metadata into a single DO. The development of the proxy was relatively simple and did not require any changes on behalf of the B2SHARE repository. CORDRA is a CNRI repository/registry/registration system that manages DO, assigns Handles to all its DOs and is accessible through DOIP. For all intents and purposes, it implements many of the features from the Digital Object Architecture.The integration of the two repositories enables copying files or movíng digital objects. In the case of copying files (metadata and bit sequences) from B2SHARE to CORDRA, for example, all functionality of the CORDRA service such as searching would become possible. Important is that in this case the PID record identifying the digital object in the B2SHARE repository would have to be extended to point to the alternative path, and the API of B2SHARE would have to offer the alternative access paths to a client. This latter aspect has not been implemented. Moving a DO from B2SHARE to CORDRA would result in changing the ownership of the PID and adding the updated information about the DO.This adaptation was not done yet, but since this archive has some special functionalities, it is interesting to discuss the way of adaptation which could be chosen. In the DOBES archive each bundle of closely related digital objects is assigned a Handle and also metadata is treated as a digital object, i.e., it has a separate Handle. For management reasons and especially for enabling different contributors to maintain control of access rights, a tree structure was developed to allow contributors to organise their data according to specific criteria and users to browse the archive in addition to execute searches on the metadata.While accessing archival objects is comparatively simple, the ingest/upload feature is more complex. It should be noted that the archive supports establishing a canonical tree of resources to define scopes for authorisation (define who has the right to grant access permissions, etc.), and facilitating lookup by supporting browsing according to understandable criteria. Therefore, depositors need to specify where in the tree the new resources should be integrated, and which initial rights are associated with them. After uploading the gathered information into a workspace, the archive carries out many checks in a micro-workflow: metadata is checked against vocabularies and partly curated, types of bit-sequences are checked and aligned with the information in the metadata, etc. An operation has been developed which is called gatekeeper to ensure a highly consistent archive despite the many (remote) people contributing to its content. Thus, the archive requires a set of 4 information units being specified:the set of bit-sequences to be uploaded,the metadata describing the bundle,the node to be used to organise the resources andthe initial rights where the default would be “open”.Adapting this archive to DOIP would imply that the proxy provides a set of operations such as “ingest a complex object”, “update metadata”, “add another bit-sequence to a specific object”, “get me the list of operations”, “give me the metadata”, etc. A client must be developed to do the front-end interaction with a user allowing them to specify the required information and to choose a suitable operation. Then the client would have to interact with the repository via DOIP by starting, for example, the gatekeeper as an external operation.

Over the past two years, the spread of COVID-19 has spurred the use of information and communication technologies (ICT) in aid of healthcare. The need to guarantee continuity to care has promoted research and industry activities aimed at developing solutions for the digitalization of the procedures to be performed to provide health services, even in emergency scenarios. Digital collection, transmission, and processing of health data represent the starting point for fulfilling this innovation process but also bring heterogeneous challenges. These motivations led to the elaboration of this work, which analyzes innovative and technological tools for the development of digital health (eHealth) through the collection of multisectoral literature, produced thanks to the cooperation of varied research groups, thus providing a multidisciplinary survey. Since digital health is expected to be one of the leading applications of the sixth-generation (6G) wireless cellular networks, this paper covers the related telecommunications aspects. Furthermore, the exploitation of artificial intelligence paradigms to elaborate massive amounts of biological data is examined. Given the extreme sensitivity of health data, this paper also investigates security and privacy issues. In particular, the main techniques and approaches to guarantee security properties (i.e., anonymity, responsibility, authentication, confidentiality, integrity, non-repudiation, and revocability) are studied. Applications involving innovative electromagnetic systems for healthcare and assisted living services are described to provide an example of an eHealth scenario leveraging ICT. Finally, the telemedicine-related regulations of the European Commission are analyzed, with particular reference to the General Data Protection Regulation (GDPR).

Sixty years have passed since the foundation and the first publishing of the Metalurgija Journal with Scientific, as well as Professional Papers and Contributions from the area of basic, applicable, and developing researching in Metallurgy and boundary metallurgy areas. The goal of the Article in Croatian and English language is to give whole the description history, organizations of Journal activities and achievements of Journal from 1962 since 2022 y, with this including List of Boards and Coworkers, were publishing total papers 3 008 ie. 2 721 Scientific and Technical and 287 Contributions, total 3 575 Authors and Co-authors from over 40 Countries. On the occasion of this Anniversary, separately with thanks for Privates, Institutions etc. for dedicated effort have managed to overcome many technical, organizational and financial problems encountered over past years.

Abstract Background The COVID-19 pandemic has presented unique challenges for rapidly designing, initiating, and delivering therapeutic clinical trials. PRINCIPLE (Platform Randomised Trial of Treatments in the Community for Epidemic and Pandemic Illnesses) is the UK national platform investigating repurposed therapies for COVID-19 treatment of older people in the community at high risk of complications. Standard methods of patient recruitment were failing to meet the required pace and scale of enrolment. This paper describes the development and appraisal of a near real-time, data-driven, ethical approach for enhancing recruitment in community care by contacting people with a recent COVID-19 positive test result from the central NHS Test and Trace service within approximately 24–48 h of their test result. Methods A multi-disciplinary team was formed to solve the technical, ethical, public perception, logistical and information governance issues required to provide a near-real time (approximately within 24–48 h of receiving a positive test) feed of potential trial participants from test result data to the research team. PRINCIPLE was also given unique access to the Summary Care Record (SCR) to ensure safe prescribing, and to enable the trial team to quickly and safely bring consented patients into the trial. A survey of the public was used to understand public perceptions of the use of test data for this proposed methodology. Results Prior to establishing the data service, PRINCIPLE registered on average 87 participants per week. This increased by up to 87 additional people registered per week from the test data, contributing to an increase from 1013 recruits to PRINCIPLE at the start of October 2020 to 2802 recruits by 20 December 2020. Whilst procedural caveats were identified by the public consultation, out of 2639 people contacted by PRINCIPLE following a positive test result, no one raised a concern about being approached. Conclusions This paper describes a novel approach to using near-real time NHS operational data to recruit community-based patients within a few days of presentation with acute illness. This approach increased recruitment and reduced time between positive test and randomisation, allowing more rapid evaluation of treatments and increased safety for participants. End-to-end public and patient involvement in the design of the approach provided evidence to inform information governance decisions. Trial registration PRINCIPLE is funded by UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research. EudraCT number: 2020-001209-22 . 26/03/2020 ISRCTN registry: ISRCTN86534580 . 20/03/2020 REC number: 20/SC/058 IRAS number: 281958

In computing, research findings are often anecdotally faulted for not being reproducible. Numerous empirical studies have analyzed the reproducibility of a variety of research. Our objective, in this study, is to quantify the current state of reproducibility of research in computing based on prior research, using three reproducibility factors—Method, Data and Experiment—to measure three different degrees of reproducibility. Twenty-five variables traditionally utilized to document reproducibility are identified and grouped into three factors, namely Method, Data and Experiment. These variables describe the extent to which these factors are documented for each paper. Approximately 100 randomly selected research papers from the International Conference on Information Systems series, for the year 2019, are surveyed. Our findings suggest that none of the papers documented all the variables. In fact, the results show that relatively few variables for each factor are documented. Some of the variables vary across different categories of papers, and most papers fail in at least one of the factors. Reproducibility scores decrease with increased documentation requirements. Reproducibility may improve over time, as researchers prioritize reproducibility and utilize methods that ensure reproducibility. Research documentation in computing is remarkably limited, resulting in a dearth of reproducible factors. Future research may study the shifts and trends in reproducibility over time. Meanwhile, researchers and publishers must increase their focus on the reproducibility aspects of their papers. This study contributes to our understanding of the status quo of reproducibility in computing research.

This paper presents a survey of the story elements in isekai (other world) manga. The large number of available isekai manga series allows the use of a survey to investigate patterns in story elements. These patterns can be used to generate hypotheses about relationships between story elements, authors’ intent, and readers’ interests. The paper begins with a review of the characteristics of isekai manga stories and places the stories into existing speculative fiction ontologies. A brief history of isekai manga and their relationships to roleplaying computer and tabletop games is provided. Finally, descriptions of the survey framework, instrument and results are presented. The survey includes data on 746 manga series identified as isekai manga by publishers or fans. The series are divided into four types (portal-quest, immersive, intrusion, and liminal). A detailed survey was performed on the 427 series identified as “portal-quest” stories (the most common type of isekai stories). The survey results are captured in a database of story elements that is organized based on plot points dictated by the form of the portal-quest stories. The survey found that the majority of the manga series are inspired by first-person shônen and otome computer games. The characteristics of the stories vary with the gender and age of the protagonists (here taken as surrogates for the gender and age of the stories’ target audiences) and this variation allows the generation of hypotheses on the motivations and interests of the different reader demographics and how they are satisfied by the stories.

A supply chain ecosystem is a collection of complex asynchronous events. Blockchain has already found commercial applications in the SC domain, particularly in product tracing and verification. However, there is a lack of uniformity in these approaches. Application-generated data cannot be accessed across the supply chain ecosystem, resulting in data silos. Data silos reduce the opportunity for supply chain process optimizations. This paper does not propose any supply chain solution but a generic framework primarily aimed at reducing the communication gaps among the stakeholders and application developer(s) to build quality solutions. The ideal readers are who want to blockchanify their existing supply chain applications. The proposed framework can add real value to the organization by developing effective SC solutions satisfying application requirements. The framework consists of four stages. In the first stage, it extracts the application requirements and then maps on blockchain following an asynchronous mode of communication among the stakeholders and application developer(s). Next, it discusses how it can combine technologies to achieve the requirements stated in the first stage. Later, it discusses how to perform effective data management. Finally, it proposes a four-stage software build method that can lead to an efficient SC solution. The primary aim of this framework is to reduce communication gaps during solution development and ensure smooth operational data movement across the SC ecosystem, thanks to blockchain. The software development process also embeds eight essential features for a quality solution. The paper is concluded by discussing the technical challenges.

Argo floats have been deployed in the global ocean for over 20 years. The Core mission of the Argo program (Core Argo) has contributed well over 2 million profiles of salinity and temperature of the upper 2000 m of the water column for a variety of operational and scientific applications. Core Argo floats have evolved such that the program currently consists of more than eight types of Core Argo float, some of which belong to second or third generation developments, three unique satellite communication systems (Argos, Iridium and Beidou) and two types of Conductivity, Temperature and Depth (CTD) sensor systems (Seabird and RBR). This, together with a well-established data management system, delayed mode data quality control, FAIR and open data access, make the program a very successful ocean observing network. Here we present Part 1 of the Best Practices for Core Argo floats in terms of how users can get started in the program, recommended metadata parameters and the data management system. The objective is to encourage new and developing scientists, research teams and institutions to contribute to the OneArgo Program, specifically to the Core Argo mission. Only by leveraging sustained contributions from current Core Argo float groups with new and emerging Argo teams and users who are eager to get involved and are actively encouraged to do so, can the OneArgo initiative be realized. This paper presents a list of best practices to get started in the program, set up the recommended metadata, implement the data management system with the aim to encourage new scientists, countries and research teams to contribute to the OneArgo Program.

The rapid advancement of digital technologies has paved the way for a revolution in archaeological documentation. Since digital cameras, tablets, portable printers, drones, and other technical gadgets have become readily available and easily replaceable, this sensitive electronic equipment has become a much more common sight at excavation sites. Using Zoot in the field. Image credit: Rok Bremec, PJP d.o.o. In the not so distant past, information about small finds or stratigraphic units had to be documented on paper and later manually transferred into digital formats. The data was stored and processed using various programs, many of which were less than ideal for the task. Indeed, the process of digitalising the data was itself suboptimal and a source of many hours of extra work, which carried significant financial consequences. To alleviate these issues, we began developing a specialised program that would enable entering and combining data from different work phases and ultimately produce reports directly usable in final site publications. Enter Zoot, a database interface for entering and retrieving data such as lists, photos, 3D site models, small find details. It can process data, perform calculations, and prepare exports intended for further processing with more specialised programs. Zoot provides a framework for keeping track of and linking all graphical documentation (photos, drawings, models), small finds, and samples with the primary excavation documentation. In addition, it supports the direct retrieval of data for GIS and statistical processing. Most importantly, the program is a paperless solution designed to shorten the time of writing reports as it automatically generates catalogues (e.g. of small finds, graves). This enables researchers such as us faster data evaluation, and ultimately leads to more affordable and timely publications of our work.

'Big Data' is a misunderstood but technically definable concept; it is large volume, unstructured, heterogenous information, that is being generated at a high velocity - which normally means it is being constantly updated in real time. And, in many situations, this is very difficult to work with; an analogy might be to compare the curated content of Netflix, which is a (very) large but structured data set, with the unending chaos of YouTube content, which is Big Data. The first part of this paper considers big data, and how it is defined and used, with the second part considering how large amounts of small data can be used in sociology as applied to archaeology.

Abstract Background The health sector aims to improve health outcomes and access to healthcare. At the same time, the sector relies on unsustainable environmental practices that are increasingly recognised to be catastrophic threats to human health and health inequities. As such, a moral imperative exists for the sector to address these practices. While strides are currently underway to mitigate the environmental impacts of healthcare, less is known about how health researchers are addressing these issues, if at all. Methods This paper uses an interview methodology to explore the attitudes of UK health researchers using data-intensive methodologies about the adverse environmental impacts of their practices, and how they view the importance of these considerations within wider health goals. Results Interviews with 26 researchers showed that participants wanted to address the environmental and related health harms associated with their research and they reflected on how they could do so in alignment with their own research goals. However, when tensions emerged, their own research was prioritised. This was related to their own desires as researchers and driven by the broader socio-political context of their research endeavours. Conclusion To help mitigate the environmental and health harms associated with data-intensive health research, the socio-political context of research culture must be addressed.