Towards the Composition of Services by End-Users: A Mobile-Based Solution

[EN] Nowadays, we live surrounded by heterogeneous and distributed services that are available to people anytime and anywhere. Even though these services can be used individually, it is through their synchronized and combined usage that end-users are provided with added value. However, existing solutions to service composition are not targeted at ordinary end-users. In fact, these solutions require technical knowledge to deal with the technological heterogeneity in which they are offered to the market. To this end, the paper presents a tool-supported platform that is aided by: (1) EUCalipTool, an end-user mobile tool that implements a Domain Specific Visual Language, which has been specifically designed to compose services on mobile devices; (2) a Faceted Service Registry, which plays the role of gateway between service implementations and end-users, hiding technological issues from the latter when including services in a composition; and (3) a Generation Module, which transforms end-user descriptions into BPMN specification that are interpreted by an execution infrastructure developed for that purpose.This work has been developed with the financial support of the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDF.Valderas, P.; Torres Bosch, MV.; Pelechano Ferragud, V. (2020). Towards the Composition of Services by End-Users: A Mobile-Based Solution. 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COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available

COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy. © 2022, The Author(s).U.S. Department of Education, ED: P031S190304; Texas A and M International University, TAMIU; National Research University Higher School of Economics, ВШЭThe COVIDiSTRESS Consortium would like to acknowledge the contributions of friends and collaborators in translating and sharing the COVIDiSTRESS survey, as well as the study participants. Data analysis was supported by Texas A&M International University (TAMIU) Research Grant, TAMIU Act on Ideas, and the TAMIU Advancing Research and Curriculum Initiative (TAMIU ARC) awarded by the US Department of Education Developing Hispanic-Serving Institutions Program (Award # P031S190304). Data collection by Dmitrii Dubrov was supported within the framework of the Basic Research Program at HSE University, RF

Obstacles to the Adoption of Model-based Design within the Automotive Supply Industry

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Author Correction: COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic (Scientific Data, (2022), 9, 1, (331), 10.1038/s41597-022-01383-6)

The original version of this Article contained an error in the spelling of the author Krzysztof Hanusz, which was incorrectly given as Hanusz Krzysztof. This has now been corrected in both the PDF and HTML versions of the Article

COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy