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This paper presents a critical discussion of the processing, reliability and implications of free big data repositories. We argue that big data is not only the starting point of scientific analyses but also the outcome of a long string of invisible or semi-visible tasks, often masked by the fetish of size that supposedly lends validity to big data. We unpack these notions by illustrating the process of extracting protest event data from the Global Database of Events, Language and Tone (GDELT) in six European countries over a period of seven years. To stand up to rigorous scientific scrutiny, we collected additional data by computational means and undertook large-scale neural-network translation tasks, dictionary-based content analyses, machine-learning classification tasks, and human coding. In a documentation and critical discussion of this process, we render visible opaque procedures that inevitably shape any dataset and show how this type of freely available datasets require significant additional resources of knowledge, labor, money, and computational power. We conclude that while these processes can ultimately yield more valid datasets, the supposedly free and ready-to-use big news data repositories should not be taken at face value.

I attempted in this article to define the term of Shonin Tsukasa 商人司 which was the office created by Oda Nobunaga and was charged with overseeing merchant activities. The office of Shonin Tsukasa has been identified with those of Shonin Gashira 商人頭 and Shonin Oyakata 商人親方 in the traditional economic history. However, my analysis of Ito Sojuro Papers 伊藤宗十郎文書 makes it clear that Shonin Tsukasa differed categorically from the latter two offices. Ito Sojuro held the office of Shonin Tsukasa throughout Nobunagaʼs rule. It was most important for him to obtain the cooperation and recognition from Nobunagaʼs close retainers in order to fulfill his duties. It means that the retainers agreed that Nobunagaʼs rule extended to the merchants within their own domains and controlled the commercial activities there. Although Ito Sojuro was commissioned with the Vermillion-sealed orders issued by Nobunaga, he had to win the recognition from the retainers for the merchants to practice their business and it was his talent to enable to do it. By appointing a useful official like Ito Sojuro as Shonin Tsukasa, Nobunaga intended to launch the direct jurisdiction over the merchants and their commercial activities under the rule of the regional lords in both the provinces of Owari and Mino. From the viewpoint of the merchants, it might mean their liberation from the regulations of the guilds za 座 controlled by the regional lords at the price of the tax burden under the direct jurisdiction of Nobunaga.

Dilhara Karunaratne,1 Nisal Karunaratne,2 Jade Wilmot,3 Tim Vincent,2 Juliet Wright,2 Nadia Mahmood,4 Alice Tang,5 Amir H Sam,5 Malcolm Reed,2 David Howlett1 1Eastbourne District General Hospital, Eastbourne, BN21 2UD, UK; 2Brighton and Sussex Medical School, Brighton, BN1 9PX, UK; 3Warwick Medical School, Coventry, CV4 7HL, UK; 4Royal Sussex County Hospital, Brighton, BN2 5BE, UK; 5Imperial College London, Charing Cross Campus, London, W6 8RP, UKCorrespondence: Dilhara KarunaratneEastbourne District General Hospital, King’s Drive, Eastbourne, BN21 2UD, UKTel +44 300 151 4500Fax +44 1323 43579Email diliekaru@yahoo.co.ukAbstract: This paper describes the development and use of the bespoke digital learning resource CAPSULE (Clinical and Professional Studies Unique Learning Environment) which was launched UK wide in May 2020 to facilitate the delivery of core learning content for UK medical students during the COVID-19 pandemic. CAPSULE is a digital learning resource comprising case-based scenarios and multiple-choice questions, encompassing all undergraduate medical specialities and supported by a pan-speciality editorial board. Following the COVID-19 pandemic lockdown and loss of face-to-face learning opportunities, CAPSULE was made available to all UK medical schools in May 2020. Following a global content review and edit and UK wide rollout, over 41,000 medical students and 3200 faculty registered as users. Approximately 1.5 million cases were completed in the first 12 months of use by up to 4500 distinct monthly users. Feedback from both students and faculty has been highly positive. CAPSULE continues to be used within UK medical schools and has allowed an entire cohort of medical students to access core curriculum content and progress their studies during the COVID-19 pandemic. Future directions may include further integration into UK medical school curricula, enhancement of platform functionality and potential expansion on an international scale.Keywords: CAPSULE, COVID-19, digital learning platform, UK medical school

Handwritten Text Recognition (HTR) technology is now a mature machine learning tool, becoming integrated in the digitisation processes of libraries and archives, speeding up the transcription of primary sources and facilitating full text searching and analysis of historic texts at scale. However, research into how HTR is changing our information environment is scant. This paper presents a systematic literature review regarding how researchers are using one particular HTR platform, Transkribus, to indicate the domains where HTR is applied, the approach taken, and how the technology is understood. 381 papers from 2015 to 2020 were gathered from Google Scholar, Scopus, and Web of Science, then grouped and coded into categories using quantitative and qualitative approaches. Published research that mentions Transkribus is international and rapidly growing. Transkribus features primarily in archival and library science publications, while a long tail of broad and eclectic disciplines, including history, computer science, citizen science, law and education, demonstrate the wider applicability of the tool. The most common paper categories were humanities applications (67%), technological (25%), users (5%) and tutorials (3%). This paper presents the first overarching review of HTR as featured in published research, while also elucidating how HTR is affecting the information environment.

Preregistration is the practice of publicly publishing plans on central components of the research process before access to, or collection, of data. Within the context of the replication crisis, open science practices like preregistration have been pivotal in facilitating greater transparency in research. However, such practices have been applied nearly exclusively to basic academic research, with rare consideration of the relevance to applied and consultancy-based research. This is particularly problematic as such research is typically reported with very low levels of transparency and accountability despite being disseminated as influential grey literature to inform practice. Evidence-based practice is best served by an appreciation of multiple sources of quality evidence, thus the current review considers the potential of preregistration to improve both the accessibility and credibility of applied research towards more rigorous evidence-based practice. The current three-part review outlines, first, the opportunities of preregistration for applied research, and second, three barriers - practical challenges, stakeholder roles, and the suitability of preregistration. Last, this review makes four recommendations to overcome these barriers and maximise the opportunities of preregistration for academics, industry, and the structures they are held within - changes to preregistration templates, new types of templates, education and training, and recognition and structural changes.

This study reports on a series of focus groups of UK public library users to understand\ud how the forced closure of UK libraries, caused by the COVID pandemic, and the\ud increased use of replacement digital services affected their library use. We specifically\ud focus on digital exclusion and whether this increased as the result of physical library\ud services being inaccessible. We show that although digital exclusion did increase as the\ud result of library closures, digital exclusion was not the best way to characterise our\ud participants’ experiences and digital choices was a more suitable concept. We show\ud how public library users adapted to library closures, how they coped with these\ud closures, and how they intend to use library services in the future. Our participants\ud reported different patterns of use of digital and physical library services, had different\ud experiences of these two modes of library service, and described their value in\ud different terms. We explore what they valued in physical and digital services and show\ud how simple arguments that digital services can replace physical ones do not match the\ud experiences or wishes of those who use these services.

Funding: This study is a part of the “Equality in suburban physical activity environments, YLLI” research project (in Finnish: Yhdenvertainen liikunnallinen lähiö, YLLI). The project is being financed by the research program about suburban in Finland “Lähiöohjelma 2020-2022” coordinated by the Ministry of Environment (grant recipient: Dr. Petteri Muukkonen). Sport and exercise contribute to health and well-being in cities. While previous research has mainly focused on activities at specific locations such as sport facilities, “informal sport” that occur at arbitrary locations across the city have been largely neglected. Such activities are more challenging to observe, but this challenge may be addressed using data collected from social media platforms, because social media users regularly generate content related to sports and exercise at given locations. This allows studying all sport, including those “informal sport” which are at arbitrary locations, to better understand sports and exercise-related activities in cities. However, user-generated geographical information available on social media platforms is becoming scarcer and coarser. This places increased emphasis on extracting location information from free-form text content on social media, which is complicated by multilingualism and informal language. To support this effort, this article presents an end-to-end deep learning-based bilingual toponym recognition model for extracting location information from social media content related to sports and exercise. We show that our approach outperforms five state-of-the-art deep learning and machine learning models. We further demonstrate how our model can be deployed in a geoparsing framework to support city planners in promoting healthy and active lifestyles. Publisher PDF

With the rapid development of Industry 4.0, modern manufacturing systems have been experiencing profound digital transformation. Development of new technologies can help to improve the efficiency of production and the quality of products. With the increasingly complex production systems, operational decision-making has encountered challenges in the sustainable manufacturing process to satisfy customers and markets' ever-changing demands. Nowadays, the rule-based heuristics approaches are widely used for scheduling management in production systems, which however significantly depends on the expert domain knowledge. In this way, the efficiency of decision-making cannot be guaranteed nor meet the dynamic scheduling requirements in the job-shop manufacturing environment. In this study, we propose using deep reinforcement learning (DRL) methods to tackle the dynamic scheduling problem in the job-shop manufacturing system. The proximal policy optimization (PPO) algorithm has been used in the DRL framework to accelerate the learning process and improve performance. The proposed method has been testified within a real-world dynamic production environment, and it performs better compared with the state-of-the-art methods.&nbsp

It has been argued that UK newspaper portrayals of illicit drug use tend to be sensationalist, exaggerated, distorted, out of context (Coomber, 1994) and highly stereotypical (Power, 1989). Contrastingly, research on Australian newspaper portrayals of illicit drug use has argued that such portrayals tend largely to occur during periods of heightened public concern around specific drugs or topics, with this set against a background of largely neutral portrayals (Hughes et al., 2011). Whilst many nations are liberalising their approaches to drug use, the UK is not, so newspaper representations take on an added significance in relation to how they influence policy (Hughes et al., 2011; Silverman, 2011; UKDPC, 2012; Tieberghien, 2014; Gstrein, 2018). We revisit the debate on UK newspaper representations of drug use, looking at tabloids and broadsheets, politically left and right leaning, and whether these factors make a significant difference to how representations are articulated. In doing so, we briefly outline the concepts of occasioning and characterisation and suggest that they might be a useful addition to the analysis of drug-related newspaper stories. We examine a sample of 76 UK national newspaper articles, from three tabloids (The Mirror, The Sun, The Daily Mail) and three broadsheets (The Telegraph, The Times, The Guardian). Critical Discourse Analysis (CDA) is used to consider how representations are articulated. Non-stigmatising and sympathetic representations regarding drugs and users are found, but these are very rare. Far more common is a stigmatising discourse, featuring negative words, phrases and metaphors, articulated consistently, irrespective of whether the newspapers are tabloid or broadsheet and regardless of their political perspective. The only significant difference is that right leaning newspapers publish more of these stigmatising articles. Whilst we may suspect this to be the case, it is significant to confirm this empirically. This reality continues to impede a more informed discussion of the issues, continues to misinform governmental policy and may affect some users themselves.

Funding: This work was supported by a PhD Studentship at the University of St Andrews, jointly funded by NatureScot via the Marine Alliance for Science and Technology for Scotland (MASTS), and the Centre for Research into Ecological and Environmental Modelling. Data were collected as part of research funded by NatureScot (project 015960) and Marine Scotland (projects SP004 and SP02B0) via the Movement Ecology of Flapper Skate project. Additional funding was provided from MASTS and Shark Guardian. Catch-and-release angling is widespread, but the impacts of this practice for captured individuals are understudied, especially among elasmobranchs. Studies on sub-lethal behavioural impacts are particularly sparse, despite their importance for the interpretation of biologging data and for assessments of species’ tolerance to capture. In this study, the behavioural responses of flapper skate (Dipturus intermedius) to catch-and-release angling were described for the first time, using archival observations (depth and temperature) for 21 tag deployment/retrieval events and five recreational angling events that occurred during tagged individuals’ time at liberty from charter vessels off the west coast of Scotland in 2016–17. During capture (8–50 minutes), the changes in depth and temperature experienced by individuals typically exceeded natural variability. Post-release, behavioural change was apparent from visual inspection, regression and functional data analysis of the time series. Immediately following release, movements into deeper water and short periods of low vertical activity (usually 1–2 hours in duration) were common. However, overall average vertical activity was typically around 38% higher in the 12 hours following release than in undisturbed activity. A small number of individuals (n = 3, 14%) exhibited irregular post-release behaviour in the form of rapid, transient re-ascents towards the surface following release. Collectively, the evidence for limited, short-term behavioural changes suggests that flapper skate behaviour is relatively resilient to catch-and-release angling from charter vessels, but irregular post-release behaviour in 14% of individuals is sufficiently notable to indicate that further research is required on the impacts of this practice. This study clearly demonstrates the value of biologging data and behavioural analyses for examining the impacts of disturbance and separating ‘disturbed’ and ‘undisturbed’ behaviours in studies of animal movement. Publisher PDF

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, policy efforts and the monitoring of global goals and agendas such as the United Nation's Sustainable Development Goals (SDGs) and UN-Habitat New Urban Agenda are hindered by the unavailability of statistical and spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, and presently, there is a strong focus within the existing literature on household-level (including individual) deprivation and less on area-level deprivation and this is problematic because deprivation at the area and household-level are known to interrelate and result in multiple challenges for individuals and communities. Within this scoping review, we build on existing literature that focuses on household- or area-level deprivation to arrive at a combined understanding of how urban deprivation is defined in relation to LMIC cities. The scoping review of existing literature was used in conjunction with local stakeholder workshops to produce a framework titled “Domains of Deprivation Framework”. The Domains of Deprivation Framework conceptualizes urban deprivation at three different scales, including at the household scale, within the area scale and at the area connect scale. It includes nine domains, (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) City Governance (Area Connect scale). The Domains of Deprivation Framework is designed to support diverse urban, health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities from a holistic perspective, combining traditional data sources (e.g., surveys or census data) with new data sources (e.g., Earth Observation data).

This study investigates how research data contributes to non-academic impacts using a secondary analysis of high-scoring impact case studies from the UK’s Research Excellence Framework (REF). A content analysis was conducted to identify patterns, linking research data and impact. The most prevalent type of research data-driven impact related to “practice” (45%), which included changing how professionals operate, changing organizational culture and improving workplace productivity or outcomes. The second most common category was “government impacts”, including reducing government service costs and enhancing government effectiveness or efficiency. Impacts from research data were developed most frequently through “improved institutional processes or methods” (40%) and developing impact via pre-analyzed or curated information in reports (32%), followed by “analytic software or methods” (26%). The analysis found that research data on their own rarely generate impacts. Instead they require analysis, curation, product development or other forms of significant intervention to leverage broader non-academic impacts.

This paper discusses how the knowledge gained from information studies creates the possibility of dealing with the challenges of refugee integration. We demonstrate that a situation-focused approach creates a systemic understanding of information needs that is useful not only for the individual but also for the design of institutional responses to forced migration. We analysed findings from our research into refugee integration using the sense-making situation-gap approach and found micro- and macro-situations affecting information behaviour and use. The combined analysis of individual and contextual factors highlighted the characteristics of situations for actors, actions, interactions and events of context. We show that overarching situations faced by refugees determine individual information gap moments, and we discuss situational information behaviour in light of these findings. The findings show how a situational approach expands understanding in information studies and emphasises the depth information behaviour adds to the social and behavioural sciences.

The article conceptualizes the quality of political information and shows how the concept can be used for empirical research. I distinguish three aspects of quality ( intelligibility, relevance, and validity) and use them to judge the constituent foundations of political information, that is, component claims (statements of alleged facts) and connection claims (argumentative statements created by causally linking two component claims). The resulting conceptual map thus entails six manifestations of information quality ( component claim intelligibility, connection claim intelligibility, component claim relevance, connection claim relevance, component claim validity, and connection claim validity). I explain how the conceptual map can be used to make sense of the eclectic variety of existing research, and how it can advance new empirical research, as a guide for determining variation in information quality, as a conceptual template for the analysis of different types of political messages and their common quality deficiencies, and as a generator of new research questions and theoretical expectations.

There is a huge opportunity in mining operational data in the supply chain (SC) to support strategic segmentation decisions. This research has the objective of developing a framework to support strategic supply chain segmentation decisions. This research is exploratory in nature, with the methodology based on action research combined with a single empirical study in a large Portuguese multinational company. A data-mining project, based on the CRISP-DM methodology, is adopted to develop the product segmentation framework. The company had the strategic objective to move beyond a single make to order strategy towards a segmented SC strategy. By applying the framework, the most relevant criteria were identified (demand volume, demand variability, order corrections, delivery time window and delivery frequency). These were then used to identify four relevant segments each with a tailored SC strategy.

Video Surveillance (VS) systems are commonly deployed for real-time abnormal event detection and autonomous video analytics. Video captured by surveillance cameras in real-time often contains identifiable personal information, which must be privacy protected, sometimes along with the locations of the surveillance and other sensitive information. Within the Surveillance System, these videos are processed and stored on a variety of devices. The processing and storage heterogeneity of those devices, together with their network requirements, make real-time surveillance systems complex and challenging. This paper proposes a surveillance system, named as Multi-Level Video Security (MuLViS) for privacy-protected cameras. Firstly, a Smart Surveillance Security Ontology (SSSO) is integrated within the MuLViS, with the aim of autonomously selecting the privacy level matching the operating device's hardware specifications and network capabilities. Overall, along with its device-specific security, the system leads to relatively fast indexing and retrieval of surveillance video. Secondly, information within the videos are protected at the times of capturing, streaming, and storage by means of differing encryption levels. An extensive evaluation of the system, through visual inspection and statistical analysis of experimental video results, such as by the Encryption Space Ratio (ESR), has demonstrated the aptness of the security level assignments. The system is suitable for surveillance footage protection, which can be made General Data Protection Regulation (GDPR) compliant, ensuring that lawful data access respects individuals' privacy rights. yes

Traditional literacy skills often neglect to develop students’ critical understanding of how information and knowledge are formed, and the unequal power relations at the heart of this process (Beilin, 2005). There are deep, entrenched biases within criminology curriculum content, and empowering students to use critical information literacy skills is an important part of recognising and disrupting knowledge hierarchies in relation to race, class, and gender. This paper builds on research exploring the content of student reading lists from the curriculum of a new criminology degree programme at an English university. Focus groups and one-to-one interviews were held with 20 undergraduate criminology students to explore how students interact with the course reading lists and how they consider and engage with the sources they use. We argue for critical information literacy to be embedded within our teaching of criminology, and for lecturers and students to more pro-actively consider the sources they use.

Purpose: Recently, big data has received considerable industrial and academic attention. Social media(SM) are becoming reliable big data sources that include various information such as customer’s opinions, product reviews and trends. However, the supply chain management (SCM) field has been lagging behind other industries in adopting SM. Hence, this paper aims to explore the value of SM and its application in SCM with recommendation for future work. Methodology: This paper reviews the existing literature systematically to highlight major research works and trends by using bibliometric analysis. Findings: Our review results show that the research on SM and SCM has attracted significant attention over the decade. SM data has been used together with different analytical tools (e.g. text mining, sentiment analysis) to manage different supply chain activities (e.g. demand forecasting, production). However, the potential of SM has not been thoroughly investigated due to the inherent nature of SM data. Therefore, this study field is in its infancy. We suggest some directions can be considered for future research, e.g. sentiment indicators for SC related posts. Originality: This paper is the first attempt to systematically analyse the interaction of SM data and SCM and to highlight the new approaches of adopting SM data for improving SCM.

As is known, new technologies have profoundly changed the way content is produced, shared and disseminated. One of the most recent (and worrying) changes is the phenomenon of ‘fake news’, especially since disinformation and intentional misrepresentation of real information have started to affect individual decision-making in the political sphere. It is a worrying phenomenon because the dissemination of fake news can challenge democratic values and undermine national security. Against this background, can copyright play a role in the fight against fake news? And what is the relationship between such news and copyright in the first place? Fake news in theory falls within copyright subject matter and may often meet the requirements for protection. The paper analyses three recent examples of fake news which have been widely disseminated online – and makes the point that copyright may subsist in such news. Yet, despite such content being potentially capable of attracting protection, we propose to remove any copyright which may arise on grounds of public interest. Indeed, when a work is protected by copyright, right holders have an incentive to exploit it, as the monopoly granted to them increases the ability to extract profits out of the work, for example via licensing. This may contribute to encouraging creators of fake news to spread such content across multiple channels to reach wide audiences. Excluding copyright could therefore help make fake news less appealing. A short reference will also be made to copyright defences which may be relied on by entities and individuals who check news’ accuracy (fact-checkers) – that is, the fair use doctrine under US law and several exceptions under EU (and UK) law, namely transient use, text and data mining, criticism and review and public security. * All authors contributed equally to this manuscript and are listed alphabetically.

In this paper we reflect on the interplay and the disconnects between real and virtual heritage experiences, and the fragmented nature of digital experiences. We consider the important engagement potential that virtual interactions bring to small less visible artefacts, like clay cuneiform tablets, and, with case study examples, we imagine museums of the future where engagements unite, blend and reinforce rich heritage experiences.

Background Zygomaticomaxillary complex (ZMC) and zygomatic arch (ZA) fractures are common injuries resulting from facial trauma and frequently require surgical management (Huang et al., Craniomaxillofac Trauma Reconstr 8(4):271-6, 2015). A substantial number of post-operative functional and cosmetic complications can arise from the surgical management of these fractures. These include scarring, inadequate facial profile restoration, facial asymmetries and diplopia (Ellis et al. J Oral Maxillofac Surg 54(4):386-400, 1996; Yang et al. Oral Maxillofac Surg Clin North Am 23(1):31-45, 2011; Kloss et al. Int J Oral Maxillofac Surg 40(1):33-7, 2011). Intuitively, most of these aforementioned complications arise as a result of inadequate fracture reduction; however, current standard practice is to assess reduction post-operatively through plain radiographs or computed tomography (CT) scans. The role of intra-operative CT scanning to assess the reduction of ZMC/ZA fractures and the potential impact on complications, has thus far not been established. Methods This is a prospective randomised controlled trial currently being undertaken at the Royal Brisbane and Women’s Hospital. All patients who require operative management of their ZMC or ZA fractures are offered enrollment in the trial. The patients are randomised into two groups: interventional (intra-operative CT) and control (no intra-operative CT). All patients in each group will have post-operative radiographs taken. From these radiographs, the reduction of the ZMC and/or ZA fracture is graded by a blinded assessor. Patients will be reviewed in clinic at 1 week and 6 weeks post-surgery. During these consultations, all patients will be assessed for scarring, diplopia, facial profile restoration and need for revision surgery. Discussion Many complications associated with surgical management of ZMC and ZA fractures involve poor aesthetic results as a direct consequence of inadequate fracture reduction. Inadequate fracture reduction is predictable given that small incisions are used and only limited visualisation of the fractures is possible during the procedure. This is due to a desire to limit scarring and reduce the risk of damage to vital structures in an aesthetically sensitive region of the body. It follows that an intraoperative adjunctive tool such as a CT scan, which can assist in visualisation of the fractures and the subsequent reduction, could potentially improve reduction and reduce complications. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12616000693426. Registered on 26 May 2016. Electronic supplementary material The online version of this article (10.1186/s13063-019-3625-8) contains supplementary material, which is available to authorized users.

This paper investigates factors influencing public transport passengers’ pre-travel information-seeking behaviours in a British urban environment. Public transport traveller surveys were conducted to better understand the journey stages at which information was sought and the information sources used. A multivariate explanatory model of pre-travel information-seeking behaviour was developed using binomial logistic regression. Explanatory factors considered include socio-demographics, trip context, frequency of public transport use, information sources used, and smartphone ownership and use. Findings suggest that travel behaviour (5 + trips weekly, and

In the field of media art, mailinglists such as nettime, -empyre-, SPECTRE and CRUMB have functioned as important para-institutional formations that have influentially played host to a diverse community of artists, critics, curators, activists and academics since the 1990s. These lists, we suggest, are of particular epistemological and methodological interest for the field of internet history due to their critical and experimental nature. This stems mainly from the cultivation of highly reflexive, at times ambivalent, stance towards the technical, social and aesthetic limits of such networking activity itself. In this sense, they present unique objects of study for exploring what difference computational methods might make for understanding mailinglist cultures over time; what we refer to in this article, drawing on Wolfgang Ernst, as counting and recounting the past. Our aim in this paper is, therefore, to both introduce these lists to the emerging field of internet history and scope out medium-specific methods that take the measure of concepts, discourses, cohorts, and events that have taken place through them over time.

Open innovation and distributed ledger technology (DLT) are both based on the underlying principles of distribution and sharing. While open innovation is about sharing knowledge to improve innovation processes and performance, DLT is a distributed data ledger that is utilized to enhance efficiency, reduce costs, and ensure immutability, traceability, security, and transparency. In this paper, we investigate the barriers to open innovation currently faced by small and medium-sized companies (SMEs) that DLT can solve. To achieve this goal, we conducted semi-structured interviews with 11 experts in open innovation and DLTs from Spain, Germany, Australia, and India. The results of our exploratory study show that DLTs can help to solve several problems, including external barriers, such as problems with contracts, financing, lack of trust, raw materials, lack of information, domestic and international market limitations, IP rights, and governmental regulations as well as bureaucracy. Internal challenges include insufficient funding, organizational systems that are out of date, and lack of trust. When it comes to difficulties associated with the management of open innovation, external barriers are frequently caused by customers' demands, while internal barriers are frequently caused by organizational culture or human nature, which cannot be improved by DLTs. Finally, SMEs might face new obstacles when integrating DLTs, such as integration problems, complex transition phases, and high setup costs as well as problems with attracting and retaining qualified employees.

Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based object detectors. Concise overview of benchmark datasets and evaluation metrics used in detection is also provided along with some of the prominent backbone architectures used in recognition tasks. It also covers contemporary lightweight classification models used on edge devices. Lastly, we compare the performances of these architectures on multiple metrics., Preprint submitted to IET Computer Vision

This paper presents an Augmented Reality (AR) project for the curation of virtual museum ‘takeouts’ and DIY exhibitions. The project’s outputs include novel AR app technology demonstrators, to support co-design with museum users and stakeholders - the goal being to create easy-to-use AR apps for scholars, citizen scientists and the interested public. The apps were designed for users to create, display, animate and interact with exhibitions of selected 3D artefacts that could, for example, reflect academic specialisms for sharing with fellow researchers or could be eclectic favourites from museum visits to show to friends or to use in school activities. The overarching project ambition, was to create AR apps to support research, engagement and education and to enable visualizations of individual artefacts as well as to assemble or reconstruct artefact forms. These forms are exemplified with 3D models of a cuneiform envelope and its tablet contents, viewable either as i) separate artefacts or ii) in their original enveloped form, with the AR apps enabling animated opening and ‘X-ray views’ of the contents within. In this way, the apps can enable users to visualize individual objects or reconstructions that can comprise artefacts held in different museums. This work is complemented by Euromed 2020 Android and iPhone AR app poster papers that account for the individual app developments, whilst this paper surveys the AR context, the design decisions and the wider project goals and ambitions.

In this paper, I will argue for the relevance of certain distinctive features of messaging systems, namely those in which data (a) can be sent and received asynchronously, (b) can be sent to multiple simultaneous recipients and (c) is received as a “potentially infinite” flow of unpredictable events. I will describe the social technology of the stock ticker, a telegraphic device introduced at the New York Stock Exchange in the 1860s, with reference to early twentieth century philosophers of synchronous experience (Bergson), simultaneous sign interpretations (Mead and Peirce), and flows of discrete events (Bachelard). Then, I will show how the ticker’s data flows developed into the 1990s-era technologies of message queues and message brokers, which distinguished themselves through their asynchronous implementation of ticker-like message feeds sent between otherwise incompatible computers and terminals. These latter systems’ characteristic “publish/subscribe” communication pattern was one in which conceptually centralized (if logically distributed) flows of messages would be “published,” and for which “subscribers” would be spontaneously notified when events of interest occurred. This paradigm—common to the so-called “message-oriented middleware” systems of the late 1990s—would re-emerge in different asynchronous distributed system contexts over the following decades, from “push media” to Twitter to the Internet of Things.

Sharing research data from public funding is an important topic, especially now, during times of global emergencies like the COVID-19 pandemic, when we need policies that enable rapid sharing of research data. Our aim is to discuss and review the revised Draft of the OECD Recommendation Concerning Access to Research Data from Public Funding. The Recommendation is based on ethical scientific practice, but in order to be able to apply it in real settings, we suggest several enhancements to make it more actionable. In particular, constant maintenance of provided software stipulated by the Recommendation is virtually impossible even for commercial software. Other major concerns are insufficient clarity regarding how to finance data repositories in joint private-public investments, inconsistencies between data security and user-friendliness of access, little focus on the reproducibility of submitted data, risks related to the mining of large data sets, and sensitive (particularly personal) data protection. In addition, we identify several risks and threats that need to be considered when designing and developing data platforms to implement the Recommendation (e.g., not only the descriptions of the data formats but also the data collection methods should be available). Furthermore, the non-even level of readiness of some countries for the practical implementation of the proposed Recommendation poses a risk of its delayed or incomplete implementation.

In the past 10 years, the collaborative maps of OpenStreetMap (OSM) have been used to support humanitarian efforts around the world as well as to fill important data gaps for implementing major development frameworks such as the Sustainable Development Goals. This paper provides a comprehensive assessment of the evolution of humanitarian mapping within the OSM community, seeking to understand the spatial and temporal footprint of these large-scale mapping efforts. The spatio-temporal statistical analysis of OSM’s full history since 2008 showed that humanitarian mapping efforts added 60.5 million buildings and 4.5 million roads to the map. Overall, mapping in OSM was strongly biased towards regions with very high Human Development Index. However, humanitarian mapping efforts had a different footprint, predominantly focused on regions with medium and low human development. Despite these efforts, regions with low and medium human development only accounted for 28% of the buildings and 16% of the roads mapped in OSM although they were home to 46% of the global population. Our results highlight the formidable impact of humanitarian mapping efforts such as post-disaster mapping campaigns to improve the spatial coverage of existing open geographic data and maps, but they also reveal the need to address the remaining stark data inequalities, which vary significantly across countries. We conclude with three recommendations directed at the humanitarian mapping community: (1) Improve methods to monitor mapping activity and identify where mapping is needed. (2) Rethink the design of projects which include humanitarian data generation to avoid non-sustainable outcomes. (3) Remove structural barriers to empower local communities and develop capacity.

COVID-19 has significantly impacted young people’s lives yet little is known about the COVID-19 related sources of information they access. We performed a cross-sectional survey of pupils (11–16 years) in North Staffordshire, UK. 408 (23%) pupils responded to an online survey emailed to them by their school. Descriptive statistics were used to summarise the data. Social media, accessed by 68%, played a significant role in the provision of information, despite it not being considered trustworthy. 89% felt that COVID-19 had negatively affected their education. Gaps in the provision of information on COVID-19 have been identified.

Objective: To compare the findings from a qualitative and a natural language processing (NLP) based analysis of online patient experience posts on patient experience of the effectiveness and impact of the drug Modafinil.Methods: Posts (n = 260) from 5 online social media platforms where posts were publicly available formed the dataset/corpus. Three platforms asked posters to give a numerical rating of Modafinil. Thematic analysis: data was coded and themes generated. Data were categorized into PreModafinil, Acquisition, Dosage, and PostModafinil and compared to identify each poster's own view of whether taking Modafinil was linked to an identifiable outcome. We classified this as positive, mixed, negative, or neutral and compared this with numerical ratings. NLP: Corpus text was speech tagged and keywords and key terms extracted. We identified the following entities: drug names, condition names, symptoms, actions, and side-effects. We searched for simple relationships, collocations, and co-occurrences of entities. To identify causal text, we split the corpus into PreModafinil and PostModafinil and used n-gram analysis. To evaluate sentiment, we calculated the polarity of each post between −1 (negative) and +1 (positive). NLP results were mapped to qualitative results.Results: Posters had used Modafinil for 33 different primary conditions. Eight themes were identified: the reason for taking (condition or symptom), impact of symptoms, acquisition, dosage, side effects, other interventions tried or compared to, effectiveness of Modafinil, and quality of life outcomes. Posters reported perceived effectiveness as follows: 68% positive, 12% mixed, 18% negative. Our classification was consistent with poster ratings. Of the most frequent 100 keywords/keyterms identified by term extraction 88/100 keywords and 84/100 keyterms mapped directly to the eight themes. Seven keyterms indicated negation and temporal states. Sentiment was as follows 72% positive sentiment 4% neutral 24% negative. Matching of sentiment between the qualitative and NLP methods was accurate in 64.2% of posts. If we allow for one category difference matching was accurate in 85% of posts.Conclusions: User generated patient experience is a rich resource for evaluating real world effectiveness, understanding patient perspectives, and identifying research gaps. Both methods successfully identified the entities and topics contained in the posts. In contrast to current evidence, posters with a wide range of other conditions found Modafinil effective. Perceived causality and effectiveness were identified by both methods demonstrating the potential to augment existing knowledge.

This paper reports an approach to addressing library anxiety by evaluating user confidence in information literacy using a red/amber/green “traffic light” tool. It discusses the development of the tool which takes elements of a more complex toolkit and adapts them for library use. It then outlines the learning from use of the tool, discusses potential pitfalls with its use and considers the benefits of adopting this innovation.