Analytical Services Research Articles

Data Management in Digital Twins for the Oil and Gas Industry: beyond the OSDU Data Platform

Competitiveness in the Oil and Gas (O&G) sector has required high technological investments for datacentric decisions. One of the trends is the adoption of Digital Twins (DTs), which use virtual spaces and advanced analytical services to monitor and improve physical spaces. Central to the interconnection of these systems is a Data Fusion Core (DFC) component, which provides data management capabilities. Although the literature has proposed data management functionality in the scope of specific O&G DT applications, different joint efforts towards standardization can be found to deal with data integration and interoperability in the industry. The Open Subsurface Data Universe (OSDU) data platform is an initiative by several partners members of The Open Group consortium created to eliminate data silos in the O&G ecosystem and leverage innovation through a data-driven approach. In this article, we look at the convergence of this effort in providing data management functionalities for digital twins, highlighting strengths, gaps, and opportunities. We investigated the extent to which the OSDU data platform meets the needs of a DFC implementation, with a focus on interoperability, integration, governance, and data lineage. We also propose additional resources for data management in this context, namely data enrichment, workflows, and data lineage. Our main contributions are: (i) analysis of possible data management capabilities for creating a working DFC for an O&G DT and (ii) initial ideas on the complementary role of OSDU data representation and ontologies and how this semantic enrichment can be leveraged in a DFC of a DT.

Optimizing Looking and Buying on Instagram: Tracing the Platformization of Advertising and Retail on Mobile Social Media

Over its first decade Instagram became central to Facebook’s dominance of audience and advertising markets. In this article, we critically examine how marketing and advertising trade press documented the development of advertising and retail on the platform. Instagram’s platformization involved formalizing relationships among users, influencers, creators, advertisers, retailers, and analytics services. The development of advertising and retail on the platform was characterized by open-ended third-party experimentation and innovation, which was gradually incorporated into, and controlled by, the platform. Advertisers and marketers increasingly approach the platform not just as an advertising service, but an end-to-end advertising, analytics and retail infrastructure. While much attention has been given to the promotional and influencer culture of Instagram, advertisers and marketers saw it as an opportunity to integrate advertising with retail. We argue that Instagram has platformized practices of looking and buying historically associated with department stores, malls, home shopping, and catalogs.

The service-based model of educational organization’s library

Theoretical, regulative and organizational foundations for developing e-libraries are discussed along with the experience of their operation in educational systems in Russia and worldwide. The author definesthe digital (electronic) library of an educational institutionas the integrated organizational, software and technological tools to support educational activities, computerize key library and information processes, integrated at the level of user data with library and information services within the e-libraries and public libraries, digital educational resources and platforms.When building the model of digital (electronic) library, educational organizations are recommended to apply service-based approach so to structurize the list of services of information acquisition, processing, storage, representation and delivery to library users, e. g. students, pedagogues, parents and administrators. The minimum requirements, including these used in the related information systems, to data within the service-based model are determined; the repertory of analytical digital services for assessing, forecasting and modelling of educational activities, is suggested. These approaches are efficient in digital transformation of libraries and building of digital (electronic) libraries within the structure of educational environment.

Twitter Poll as a Medium for Questionnaire-Based Health Survey: An Experience of a Pilot Study on the Preference of Systems of Medicine for Various Health Conditions.

BackgroundThe easy accessibility of smartphones and internet connections enables people to stay virtually connected to communities via social media. However, social media is also being explored for health care education and dissemination of health-related information. Twitter (Twitter, Inc., San Francisco, California) is one of the popular social media used for spreading health-related information. Twitter enables users to create polls to get opinions from their users. The Twitter poll is a less-explored avenue for health surveys.ObjectiveIn this pilot study, we aimed to explore the feasibility of conducting a questionnaire-based health survey (on the preference of different systems of medicine for the treatment of various health problems) as a Twitter poll.MethodsThis observational study was conducted on Twitter for five consecutive days starting from May 31, 2021. We posted five Twitter polls, one poll each day, for five days in a #INPST unique Twitter campaign. Preferences on the use of modern medicine, traditional medicine, a combination of these two systems, and self-medication were collected on five health conditions. We collected the data from the landing poll page and Tweet Analytics (insight about the engagement of tweets provided free by Twitter). The Chi-square test, binomial test, and one-way Analysis of Variance were used to compare data, and Spearman's rank correlation coefficient was used to find a correlation between categorical variables.ResultsWe had a mean 4358.6±590.3 poll reach with the engagement of 108.2±36.87 Twitter users and 67.6±28.06 votes. Most of the responses were received on the first day of posting the poll. The participation then gradually decreased. Modern medicine was the first choice for emergency medical care (85.1%, P <0.0001), treatment of cancer (43.6%, P <0.0001), and sexual disorder or transmitted diseases (48.9%, P <0.0001). Traditional medicine was the first choice (37.5%, P = 0.63) for the treatment of common illnesses, and a combination of modern and traditional medicine was the first choice (37.5%, P = 0.01) for the treatment of chronic diseases.ConclusionA medical survey with short questions with a maximum of four response options can be conducted on Twitter. Survey results can be obtained without any third-party analytic service. The response rate is highest on the first day and participation may decrease when multiple polls are posted within a Twitter campaign. Preference for systems of medicine found in this study can be used for designing large-scale surveys in the future.

Food analysis: a practical guide

Food analysis: a practical guide

A Semantic Web-Enabled Approach for Dependency Management

The use of external libraries in today’s software projects allows developers to take advantage of features provided by such application programming interfaces (APIs) without having to reinvent the wheel. However, APIs have also introduced new challenges to the software engineering community (e.g. API incompatibilities, software vulnerabilities, and license violations) that extend beyond traditional project boundaries and often involve different software artifacts. One potential solution to these challenges is to provide a technology-independent representation of software dependency semantics and its integration with knowledge from other software artifacts. In our research, we take advantage of the semantic web (SW) and its technology stack to establish a unified knowledge representation of build and dependency repositories. Given this knowledge base, we can now extend and integrate other (heterogeneous) resources to allow for a flexible and comprehensive global impact analysis approach. To illustrate the applicability of our SW-enabled modeling approach, we discuss two different applications. These applications illustrate how our modeling approach can not only integrate and reuse knowledge from dependency management systems and other software artifacts, but also take advantage of inference services provided by the SW to support novel software analytics services across artifact and project boundaries.

Интеграция предиктивно-аналитических моделей с IoT-платформой цифрового экомониторинга

The research focuses on the development of applied software systems for automated environmental monitoring. The task of developing and integrating applied software, in particular calculation and analytical models based on machine learning (ML) methods, with an IoT platform of digital eco-monitoring for industrial enterprises is considered. Such a platform is used to create software and hardware systems of CEMS – Continuous Emissions Monitoring System class, designed for continuous monitoring of pollutant emissions into the atmospheric air at production facilities. Use of ML tools integrated with the platform allows to expand significantly the functionality of the existing CEMS, in particular to quickly build new SaaS services for forecasting the dynamics of pollution distribution. Given the high requirements for industrial systems, there is a need to create a specialized software product – an analytical server that implements the management of connected predictive analytical ML models with the required level of service quality, including automatic initialization of new analytical scripts as classes, isolation of individual components, automatic recovery after failures, data security and safety. The paper proposes a scheme of functional and algorithmic interaction between the IoT platform of digital eco- monitoring and the analytical server. The proposed implementation of the analytical server has a hierarchical structure, at the top of which is an application capable of accepting high-level REST requests to initialize calculations in real time. This approach minimizes the impact of one analytical script (class) on another, as well as extending the functionality of the platform in "hot" mode, that is, without stopping or reloading. Results demonstrating automatic initialization and connection of basic ML models for predicting pollutant concentrations are presented.

ICES Data and Analytic Services: Eight Years Young.

ObjectiveIn March 2014, ICES launched Data &amp; Analytic Services (DAS), expanding the access to ICES data and analytics beyond ICES scientists and analytic staff. In eight years, DAS has grown and evolved to increase high quality services offered to an expanding client base of external researchers.&#x0D; ApproachAt the inception of DAS, two services were offered to public sector researchers: data access and analytics. Data access enabled researchers to analyze coded record-level data through a secure virtual environment. Analytics, conducted by DAS staff in ICES analytic environment, provided researchers with risk-cleared summary level reports. In response to growing demand from an increasingly diverse range of researchers, ICES engaged in extensive consultations with internal and external stakeholders to re-evaluate and operationalize new services. Compliance with contractual obligations and Ontario law, organizational capacity to scale up, alignment with ICES’ mission, vision and values, were cornerstones in establishing new offerings.&#x0D; ResultsAnalytic services became available to private sector researchers in June 2016. In March 2017, support for cohort and longitudinal follow-up studies became the newest service offering (researchers provided with a list of applicable individuals defined for the purposes of conducting publicly funded research). As more data assets become available to researchers, requests continue to increase in volume and complexity, particularly of projects seeking to import external data for linkage to ICES data. A second high performance computing virtual environment onboarded researchers September 2021 while the original analytic environment has undergone multiple upgrades, and will soon be fully refreshed. Regular solicitation of feedback has enabled DAS to increase staffing and diversify resources available which improves the client experience at all stages.&#x0D; ConclusionsSince its inception, DAS has expanded from five to thirty personnel, grown and diversified its new and returning client base and has responded to demand for new services. DAS continues to provide high quality services which enable impactful research and is responsive to new opportunities for collaboration and service provision.

UNITE Species Hypotheses Matching Analysis

UNITE (User-friendly Nordic ITS Ectomycorrhizal Database) (Nilsson et al. 2018) is a theoretical and practical platform for calculating, identifying and communicating DNA-based species hypotheses that may not have been described as formal species yet. UNITE species hypotheses (SH) matching analysis is a digital service for the global species discovery from environmental DNA (eDNA). SH matching service is based on UNITE datasets hosted in PlutoF. The tool places a user's unknown DNA sequences in FASTA format into existing UNITE species hypotheses and forms SHs not yet present in the system. Its output in a series of CSV and HTML files (Fig. 1) includes information about what species are present in eDNA samples, whether they are potentially undescribed new species, where they are found in other studies, whether they are alien or threatened species, etc. The service is very useful for understanding species distribution patterns, host range, etc. Analysis output will provide Digital Object Identifier (DOI)-based stable identifiers for communicating species hypotheses found in eDNA. DOIs are connected to the taxonomic backbone of PlutoF and GBIF (Global Biodiversity Information Facility). In this way every DOI is accompanied by a taxon name, which is still widely used for the communication of species. In the case of undescribed species, DOIs will be issued by the PlutoF system. All UNITE services are focused on fungi but cover all Eukarya by using publicly available rDNA ITS (ribosomal DNA Internal Transcribed Spacer) marker sequences accompanied by sample metadata. SH matching analysis results can be published in GBIF as DNA-derived occurrence data where occurrences are linked to SH identifiers present in GBIF backbone taxonomy. Source code of the SH matching analysis tool is available in GitHub with an implementation accessible online on the PlutoF platform for registered users. PlutoF (Abarenkov et al. 2010) is an open data management platform for biology and related disciplines. Users can manage their bodiversity datasets through a full data life cycle—from uploading to publishing and archiving in FAIR (Findable, Accessible, Interoperable, Reusable) way. PlutoF also features an analysis module by providing analytical services for molecular sequence identification and species discovery from eDNA samples. There are more than 8 000 registrered users in PlutoF with more than 500 users who have used its analysis module (as of August, 2022).

Automatic Distributed Deep Learning Using Resource-Constrained Edge Devices

Processing data generated at high volume and speed from the Internet of Things, smart cities, domotic, intelligent surveillance, and e-healthcare systems require efficient data processing and analytics services at the Edge to reduce the latency and response time of the applications. The fog computing edge infrastructure consists of devices with limited computing, memory, and bandwidth resources, which challenge the construction of predictive analytics solutions that require resource-intensive tasks for training machine learning models. In this work, we focus on the development of predictive analytics for urban traffic. Our solution is based on deep learning techniques localized in the Edge, where computing devices have very limited computational resources. We present an innovative method for efficiently training the gated recurrent-units (GRUs) across available resource-constrained CPU and GPU Edge devices. Our solution employs distributed GRU model learning and dynamically stops the training process to utilize the low-power and resource-constrained Edge devices while ensuring good estimation accuracy effectively. The proposed solution was extensively evaluated using low-powered ARM-based devices, including Raspberry Pi v3 and the low-powered GPU-enabled device NVIDIA Jetson Nano, and also compared them with Single-CPU Intel Xeon machines. For the evaluation experiments, we used real-world Floating Car Data. The experiments show that the proposed solution delivers excellent prediction accuracy and computational performance on the Edge when compared to the baseline methods.

How clinical toxicology service can contribute in forensic cases?

To present the contribution of clinical toxicology service in forensic cases investigations. Poisons control centers (PCC) are medical units that works mainly with clinical toxicology. They exist to provide advice to the public, physicians and others on the toxicity of and management of poisoning, caused by medicaments, drugs of abuse, chemicals, commercial products and venoms. Other attributions to the PCC include clinical and laboratory diagnosis, notification of intoxication cases, control and distribution of antidotes. The service should be available 24 hours a day, 365 days a year, and be staffed by multiprofessional team which guarantee coverage in clinical and laboratory support. A clinical toxicologist plays an important role in multiple areas of clinical medicine. By providing consultative services, clinical toxicologists facilitate the best treatment plan for patients present at the emergency department for the treatment of an acute toxic exposure of accidental or intentional nature. In many cases the causative agent is unknown, thus an analytical toxicology laboratory service is crucial to the operation of a clinical toxicology center. The tasks may cover besides support for diagnosis and prognosis of poisonings, help for indication for (invasive) treatment, monitoring of the efficiency of detoxication and support in differential diagnostic exclusion of poisonings. Furthermore, patients addicted to alcohol, medicaments or drugs of abuse have to be monitored. For the other hand, but not so distant, forensic toxicology pertains to the practice of toxicology in the medicolegal realm including investigation of causes of death, driving under the influence of drugs, child protection services, drug-facilitated crime, doping control, bioterrorism, and environmental exposures. This presentation was based on the management of clinical cases of Campinas Poison Control Center (Campinas, Brazil), with outcome in forensic investigation. In most of clinical toxicology cases, the end-user is physician using the emergency toxicology laboratory findings to treat and care for an intoxicated or poisoned patient, while in forensic toxicology, the end-user can be a physician or a non-medical professional such as a lawyer, or law enforcement agent using the results to interpret a cause of death or the forensic event. Nevertheless, some circumstances of clinical intoxication cases such as suicide and homicide attempt, drug abuse, drug-facilitated sexual assault, child abuse, chemical disasters, bioterrorism and chemical warfare agents will develop into a forensic investigation. Therefore when a forensic case was previously assisted by a PCC some advantages can be listed in benefit of fulfilled the investigation, such as: (a) fully data of case, especially signs and symptoms, story, exposed dose, applied treatment (antidote) and clinical laboratory exams; (b) collection of biological samples during the “peak of effects” (blood: Cmax; urine: few hours after exposure); (c) confirmation of diagnosis of intoxication/poisoning. In fatal cases of intoxication (caused by pesticides, NPS, chemicals and animal venoms) previously assisted by PCC, patient's normally remain hospitalized more than 1 week, resulting in false-negative detection in postmortem samples analysis, thus the confirmation of diagnosis by a PCC laboratory, medical data report and hospital samples will be an important tool to contribute in forensic intoxication cases. While clinical toxicology professionals interact with medical and clinical laboratory professionals who most commonly practice in a hospital-based setting, forensic toxicology professionals interact with, coroner's law enforcement officers, and the judicial system. The analytical aspects of both clinical and forensic toxicology practice are convergent and involve similar workflow approaches thus the partnership between them toxicology will result in increase of the success of the investigations.

Sodium nitrite poisoning; A case series of 15 fatalities

To highlight a recent surge in new drug deaths resulting from sodium nitrite (NaNO2) toxicity in which the post mortem blood nitrite (NO2-) and nitrate (NO3) concentrations were measured. The University Hospitals of Leicester (UHL) NHS Trust post-mortem toxicology service receives samples from 27% of Her Majesty's Coroners in England and Wales, analysing approximately 4000 cases per year. We report a series of 15 cases, spanning an 18-month period, in which NaNO2 was the suspected cause of death. NaNO2 is an inorganic sodium salt that has several industrial applications, the most common being preserving meat products. Excess NaNO2 ingestion has also been associated with severe toxicity/death when consumed in excess either accidentally or intentionally. Recently, suicide kits containing NaNO2, and an anti-emetic drug, to assist with ingestion of NaNO2, have become available online. Excessive nitrite ingestion results in iron oxidation within haemoglobin and subsequent production and accumulation of methaemoglobin. Methaemoglobin cannot bind or transport oxygen effectively therefore severe tissue hypoxia and death result. Nitrite is also a vasodilator and can cause coronary ischaemia and stroke as a result of hypotension, tachycardia, and hypoxia. Routine screening was performed on post mortem blood samples received as per usual laboratory protocol; including ethanol analysis by Headspace Gas Chromatography–Flame Ionisation Detection (HS GC-FID), drug screening by High Resolution Accurate Mass–Mass Spectrometry (HRAM-MS) and confirmatory drug quantitation by Liquid Chromatography–Tandem Mass Spectrometry (LC-MS/MS). In this series, the majority of case histories described the presence of NaNO2 at the scene of death/purchase of a suicide kit; therefore aliquots of post mortem blood were referred to a specialist laboratory (William Harvey Research Institute) for quantitative nitrite and nitrate analysis. Measurement was based upon the gas-phase chemiluminescent reaction between nitric oxide (NO) and ozone (O 3 ); NO levels were determined using an NOA 280A, Sievers NO analyser. Fifteen post-mortem cases in which NaNO2 ingestion was considered the most probable cause of death were reported between January 2020 to July 2021; mean age 31 years (range 18 to 49), 8/15 (53%) male. In almost all cases the clinical history described mental health issues, depression, previous suicide attempts/overdose, self-harm or suicidal ideation. Two thirds of the cases listed prescribed anti-depressants/anti-psychotics; these drugs were detected in 6/15 cases. Ethanol was detected in 3/15 cases and anti-emetic drugs in 3/15 cases. Illicit drugs were present in two of the cases at concentrations suggestive of prior use. The mean nitrite and nitrate concentrations were 2106 μmol/L (min–max 1.4–8100) and 7818 μmol/L (14.5–21,100) respectively. Blood reference ranges for nitrite and nitrate are 0.1–0.4 and 20–40 μmol/L respectively. Nitrite was elevated in all but one case, nitrate was elevated in 12/15 (80%) cases. For the majority of cases (9/15) individuals were discovered deceased; 4/15 cases emergency services attended and death occurred either on route to or following hospital admission. The remaining two cases gave insufficient detail regarding circumstances of death. One post mortem report described discolouration on post mortem consistent with the presence of methaemoglobinaemia. The detection and quantitation of nitrite and nitrate during post-mortem toxicological investigations represents a significant challenge analytically and heavily relies upon circumstantial evidence. Even though it still remains a rare cause of death, it is worthwhile considering the possibility of sodium nitrite use in individuals with suicidal ideation given its apparent availability online. The provision of a quantitative nitrite/nitrate analytical service greatly assists in determining the cause of death in these cases.

An illicit drug early warning system in Victoria, Australia: The role of forensic toxicology in clinical casework

In response to the evolving threat of illicit substance use in Australia, public health bodies and advisory committees have called for an enhanced public health response including greater visibility related to community illicit drug use, particularly novel psychoactive substances (NPS). Victorian state government agencies recommended the development of a state-wide illicit drug early warning system (EWS), utilising data-sharing collaborations between emergency physicians, forensic laboratories, researchers, and health services. Current monitoring modalities utilised in Australia, such as surveys, wastewater monitoring and coronial investigations, lack the specificity and/or responsiveness required for an effective EWS. Clinical toxicity observed in patients presenting to emergency departments (EDs) following exposure to an illicit drug provides an objective and timely measure of harm. Although illicit drug EWS exist in other jurisdictions, not all utilise high-quality forensic analysis and instead rely on patient-reported exposure. However, there is evidence demonstrating poor correlation between reported exposure and forensic analytical findings. The Emerging Drugs Network of Australia Victoria (EDNAV) was therefore created to provide a clinical registry collecting high-quality clinical and analytical data from Emergency Department (ED) illicit drug presentations, combined with a multi-disciplinary expert team to analyse registry data and provide intelligence to a state illicit drug EWS. The EDNAV is a Human Research Ethics Committee (HREC) approved project created in conjunction with a pilot project utilising data from wastewater analysis, syringe residue analysis and ED illicit drug presentations to provide health authorities with intelligence on community drug use. Patients 16 years of age or older presenting to one of eleven EDNAV project EDs with reported or suspected illicit drug related toxicity requiring a venipuncture as part of their standard clinical care are eligible for registry inclusion. Blood samples from cases are transferred weekly to the Victorian Institute of Forensic Medicine (VIFM) Toxicology Department. Overnight liquid chromatography-tandem mass spectrometry (LC-MS/MS) screens for 327 common pharmaceuticals and illicit substances (including ∼80 NPS), followed by a secondary NPS specific screen targeting 268 NPS. The NPS specific screen is actively updated based on emerging drug intelligence and literature reports. The HREC approved waiver of patient consent to include deidentified clinical and analytical data into a purpose built secure on-line (REDCap platform) registry. Forensic and clinical toxicologists/emergency physicians produce intelligence reports based on EDNAV registry data, which are provided to department of health policy officers to identify triggers and/or threats that lead to interventions designed to reduce community harm. There were 700 ED illicit drug presentations included in the EDNAV registry during the period September 2020–February 2022 (71% male, median age 33 years). Eighty-seven percent of patients arrived in ED via ambulance. Overall clinical acuity was high with 22% Australasian triage category 1 (require immediate treatment), and 62% category 2 (require treatment within 10 minutes), while 47% of patients were classified as having moderate, and 41% severe clinical toxicity. In additional to traditional illicit substances, novel substance detections included illicit benzodiazepines ( n = 10), cathinones ( n = 9), synthetic cannabinoid receptor agonists ( n = 6), and opioids ( n = 3). Forensic analyses revealed that in over 90% of cases there were different and/or additional drugs detected in comparison to the reported exposure, suggesting significant drug adulteration, drug substitution or under-reporting and highlighting the potential limitations of illicit drug EWS that do not utilise high-quality forensic analysis. Three public health alerts have been released in Victoria as the result of EDNAV registry intelligence, involving detections of N-ethylpentylone, 25B-NBOH, and paramethoxymethamphetamine. The EDNAV registry project has highlighted the critical role of a high-quality forensic analytical service in an illicit drug EWS in the state of Victoria.

Caregiver-Implemented Digital Activity Schedules With Virtual Coaching.

During the COVID-19 pandemic, many insurance companies approved the funding of telehealth-based behavior analytic services for both training and direct-care purposes. Activity schedules are a simple and effective intervention that can be used in the home environment to improve independence for children with ASD. Recent efforts have shifted the format of activity schedules from paper-based schedules to digital platforms that make the schedules more portable and provide easier access for both the caregiver and the Board Certified Behavior Analyst (BCBA). Google Slides® is a readily available web-based platform that has been used to design and deliver behavior analytic instruction during the COVID-19 pandemic. A non-concurrent multiple baseline design across three child-caregiver dyads was used to evaluate the effectiveness of a caregiver-implemented digital activity schedule intervention on the independent play behaviors of children with ASD. The activity schedule was created and shared on the Google Slides® platform and caregivers received bug-in-ear (BIE) coaching from practitioners to implement the intervention. Regardless of some minor treatment implementation difficulties attributed to the remote service delivery and the digital format, the digital platform and coaching intervention were effective in increasing independent schedule following with minimal training on the part of the caregiver. We hope that the results of this study provide BCBAs with additional guidance on effective interventions and procedures for remote service delivery.

Is “Choose One” Policy Profitable?

Some platforms with superior digital analytics service technology ask users to ``choose one of two platforms'' to restrict users’ homing choices. We develop a game-theoretic model in a duopoly setting to investigate the impacts of the ``choose one'' policy and asymmetry in digital analytics service technology on platform competition. We first examine how the asymmetry in digital analytics service technology influences equilibrium market demands, prices, and profits of the two platforms under four different users' homing scenarios. We find that under scenarios influenced by the ``choose one

Impact factions: assessing the citation impact of different types of open access repositories

Institutional repositories (IR) maintained by research libraries play a central role in providing open access to taxpayer-funded research products. It is difficult to measure the extent to which IR contribute to new scholarship because publisher self-archiving policies typically require researchers to cite the “version of record” of a manuscript even when an IR copy is accessed to conduct the research. While some studies report an open access (OA) citation advantage resulting from the availability of self-archived or “green” OA manuscripts, few have sought to measure an OA citation effect of IR separately from disciplinary repositories, including arXiv and PubMed Central. In this study, the authors present a bibliometric analysis examining correlations between search engine performance of items in IR, OA availability from different types of repositories, and citations. The analysis uses a novel, open dataset of IR access and usage derived from five months of Google search engine results pages (SERP) data, which were aggregated by the Repository Analytics and Metrics Portal (RAMP) web service. Findings indicate that making OA copies of manuscripts available in self-archiving or “green” repositories results in a positive citation effect, although the disciplinary repositories within the sample significantly outperform the other types of OA services analyzed. Also evident is an increase in citations when a single manuscript is available in multiple OA sources.

The state of information infrastructure for global climate governance

PurposeThe world is facing global challenges that require international collaboration. This study aims to describe and analyze how digital technologies are applied in global governance to respond to such critical challenges.Design/methodology/approachThe authors apply an interpretive case study of climate reporting to the United Nations Framework Convention on Climate Change (UNFCCC) as a case of digitalization in global governance. It includes interviews with officials in the Swedish public administration and the UNFCCC secretariat to cover national and international levels. The authors describe the reporting process and analyze the role of information systems through the lens of information infrastructures.Findings“Information infrastructure” is a valuable instrument to understand digitalization in global governance as a complex interplay between information systems, information, standards, organizations, people and social structures. The level of sophistication is, however, basic with a large potential for improvement – for instance in analytical and communicative services to support evidence-based decision-making and assessment of progress.Research limitations/implicationsThe data collection is limited to one governance process: reporting. Future studies should complement the findings by broadening the scope to other processes. The authors propose that digital global governance is dependent on an effective information infrastructure, and that the five design principles by Hanseth and Lyytinen (2016) offer guidance when developing this.Practical implicationsThe results indicate a large unutilized potential of digital technologies to improve progress assessment, communicate more effectively with stakeholders and identify new ways of visualizing data to support decision making in global climate policy.Social implicationsUse of digital technologies, as suggested in the article, could strengthen the implementation capability of climate goals, which is of urgent need.Originality/valueWhile most research in digital governance considers the national or municipal level, this study provides empirical insight and theorization of digital technologies in a global governance setting.

Deployment of an End-to-End Remote, Digitalized Clinical Study Protocol in COVID-19: Process Evaluation.

BackgroundThe SARS-CoV-2 (COVID-19) pandemic may accelerate the adoption of digital, decentralized clinical trials. Conceptual recommendations for digitalized and remote clinical studies and technology are available to enable digitalization. Fully remote studies may break down some of the participation barriers in traditional trials. However, they add logistical complexity and offer fewer opportunities to intervene following a technical failure or adverse event.ObjectiveOur group designed an end-to-end digitalized clinical study protocol, using the Food and Drug Administration (FDA)–cleared Current Health (CH) remote monitoring platform to collect symptoms and continuous physiological data of individuals recently infected with COVID-19 in the community. The purpose of this work is to provide a detailed example of an end-to-end digitalized protocol implementation based on conceptual recommendations by describing the study setup in detail, evaluating its performance, and identifying points of success and failure.MethodsPrimary recruitment was via social media and word of mouth. Informed consent was obtained during a virtual appointment, and the CH-monitoring kit was shipped directly to the participants. The wearable continuously recorded pulse rate (PR), respiratory rate (RR), oxygen saturation (SpO2), skin temperature, and step count, while a tablet administered symptom surveys. Data were transmitted in real time to the CH cloud-based platform and displayed in the web-based dashboard, with alerts to the study team if the wearable was not charged or worn. The study duration was up to 30 days. The time to recruit, screen, consent, set up equipment, and collect data was quantified, and advertising engagement was tracked with a web analytics service.ResultsOf 13 different study advertisements, 5 (38.5%) were live on social media at any one time. In total, 38 eligibility forms were completed, and 19 (50%) respondents met the eligibility criteria. Of these, 9 (47.4%) were contactable and 8 (88.9%) provided informed consent. Deployment times ranged from 22 to 110 hours, and participants set up the equipment and started transmitting vital signs within 7.6 (IQR 6.3-10) hours of delivery. The mean wearable adherence was 70% (SD 19%), and the mean daily survey adherence was 88% (SD 21%) for the 8 participants. Vital signs were in normal ranges during study participation, and symptoms decreased over time.ConclusionsEvaluation of clinical study implementation is important to capture what works and what might need to be modified. A well-calibrated approach to online advertising and enrollment can remove barriers to recruitment and lower costs but remains the most challenging part of research. Equipment was effectively and promptly shipped to participants and removed the risk of illness transmission associated with in-person encounters during a pandemic. Wearable technology incorporating continuous, clinical-grade monitoring offered an unprecedented level of detail and ecological validity. However, study planning, relationship building, and troubleshooting are more complex in the remote setting. The relevance of a study to potential participants remains key to its success.

GA-IRACE: Genetic Algorithm-Based Improved Resource Aware Cost-Efficient Scheduler for Cloud Fog Computing Environment

The ever-growing number of Internet of Things (IoT) devices increases the amount of data produced on daily basis. To handle such a massive amount of data, cloud computing provides storage, processing, and analytical services. Besides this, real-time applications, i.e., online gaming, smart traffic management, and smart healthcare, cannot tolerate the high latency and bandwidth consumption. The fog computing paradigm brings the cloud services closer to the network edge to provide quality of service (QoS) to such applications. However, efficient task scheduling becomes critical for improving the performance due to the heterogeneous nature, resource-constrained, and distributed environment of fog resources. With an efficient task scheduling algorithm, the response time to application requests can be reduced along with bandwidth and cloud resource costs. This paper presents a genetic algorithm-based solution to find an efficient scheduling approach for mapping application modules in a cloud fog computing environment. Our proposed solution is based on the execution time as a fitness function to determine an efficient module scheduling on the available fog devices. The proposed approach has been evaluated and compared against baseline algorithms in terms of execution time, monetary cost, and bandwidth. Comprehensive simulation results show that the proposed approach offers a better scheduling strategy than the existing scheduler.

Cloud LMS of Statistic Data Visualization

The purpose of the article is to create a cloud LMS (Learning Management System) analysis and visualization of statistics. The research methodology is cloud information processing technologies. The novelty of the research is the implementation of a new training course on the use of modern means of data visualization in the form of cloud LMS. Conclusions. The material presented in the article gives a clear example of cloud technology usage in distance education. The materials of the training course “Information and Analytical Programs and Services” are implemented in the form of a cloud LMS based on the Google Classroom platform using a modern structure of material presentation.