Production Process Data Research Articles

Embedded reproduction in platform data work

ABSTRACT This paper focuses on the experiences of Latin American data workers who annotate data for machine learning algorithms through labor platforms. It introduces the notion of ‘embedded reproduction’: the relationship between embeddedness, the degree to which non-economic institutions and their social environment constrain socioeconomic activity, and social reproduction, or the activities that nurture, maintain, and regenerate the workforce. The analysis of 38 interviews with platform workers suggests they are situated in a highly disembedded market due to the lack of regulations on the data production process, giving free rein to platforms to set rules to their detriment. This article explores how this disembeddedness shapes social reproduction by studying three forms of collective social support received by workers: from family members, neighbors and local communities, and online groups. The support of these networks is primarily local, depends on high levels of trust, and is gendered. These findings suggest that platform data work is unsustainable from an embedded reproductive perspective since platform intermediation leads workers and local communities to carry out the social and economic risks associated with this form of gig work. This research invites a dialogue between the embeddedness framework with social reproduction as well as a consideration of the importance of nature and natural resources in the study of social environments.

A design method for an intelligent manufacturing and service system for rehabilitation assistive devices and special groups

The maturity of Industrial 4.0 technologies (smart wearable sensors, Internet of things [IoT], cloud computing, etc.) has facilitated the iteration and digitization of rehabilitation assistive devices (RADs) and the innovative development of intelligent manufacturing systems of RADs, expanding the value-added component of smart healthcare services. The intelligent manufacturing service mode, based on the concept of the product life cycle, completes the multi-source data production process analysis and the optimization of manufacturing, operation, and maintenance through intelligent industrial Internet of things and other means and improves the product life cycle management and operation mechanism. The smart product-service system (PSS) realizes the value-added of products by providing users with personalized products and value-added services, service efficiency, and sustainable development and gradually forms an Internet-product-service ecosystem. However, research on the PSS of RADs for special populations is relatively limited. Thus, this paper provides an overview of an IoT-based production model for RADs and a smart PSS-based development method of multimodal healthcare value-added services for special people. Taking the hand rehabilitation training devices for autistic children as a case, this paper verifies the effectiveness and availability of the proposed method. Compared with the traditional framework, the method used in this paper primarily helps evaluate rehabilitation efficacy, personalizes schemes for patients, provides auxiliary intelligent manufacturing service data and digital rehabilitation data for RAD manufacturers, and optimizes the product iteration development procedures by combining user-centered product interaction, multimodal evaluation, and value-added design. This study incorporates the iterative design of RADs into the process of smart PSS to provide some guidance to the RADs design manufacturers.

From Real-world Individuals' Data to National Health Indicators: Multiphase Pilot Study in Gabon.

BackgroundAchieving health goals requires informed decision-making supported by transparent, reliable, and relevant health information. This helps decision makers, such as health managers, to better understand the functioning of their health system and improve their ability to respond quickly to health demands. To achieve this, the health system needs to be supported by a digitized decision-making information system. In Sub-Saharan African countries, inadequate digital infrastructure, including limited internet connectivity and insufficient access to appropriate computer software, makes it difficult to collect, process, and analyze data for health statistics. The processing of data is done manually in this case; however, this situation affects the quality of the health statistics produced and compromises the quality of health intervention choices in these countries.ObjectiveThis study aimed to describe the conceptual approach of a data production and dissemination platform model proposed and implemented in Gabon. More precisely, it aimed to present the approach applied for the multidimensional analysis of the data production and dissemination process in the existing information system and present the results of an evaluation of the proposed model implemented in a real context.MethodsThe research was carried out in 3 phases. First, a platform was designed and developed based on the examination of the various data production and indicator generation procedures. Then, the platform was implemented in chosen health facilities in Gabon. Finally, a platform evaluation was carried out with actual end users.ResultsA total of 14 users with 12 years of average experience in health data management were interviewed. The results show that the use of the proposed model significantly improved the completeness, timeliness, and accuracy of data compared with the traditional system (93% vs 12%, P<.001; 96% vs 18%, P<.001; and 100% vs 18%, P<.001; respectively).ConclusionsThe proposed model contributes significantly to the improvement of health data quality in Gabon.

Industry 4.0 Technologies for Manufacturing Sustainability: A Systematic Review and Future Research Directions

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies.

Enabling modern data discovery for atmospheric measurements

The Atmospheric Radiation Measurement (ARM) user facility is a US Department of Energy Office of Science user facility that is managed and operated through a collaborative effort led by nine US Department of Energy national laboratories. The ARM Data Center, located at Oak Ridge National Laboratory, is responsible for the timely collection, processing, and delivery of data products to the scientific community. The ARM Data Center holds more than 11,000 data products, including metadata collected from field campaigns, instruments, value-added products, and principal investigator–contributed data. These data sets are checked for successful transfer (for most data, this transfer is carried out automatically via the network; however, some of the largest data sets and some of the most remote sites require manual shipping of hard disks) and both the data and metadata are processed to a standard format, which is an ARM-standardized structure, via the Network Common Data Form. The Network Common Data Form is a self-describing binary format with many compatible software tools. Once processed, the data are cataloged, stored in the ARM Data Archive, and made discoverable through association with an array of metadata-characterizing information, such as location and measurement classification. These metadata enable powerful search capabilities through the ARM Data Center Data Discovery interface. This paper discusses the workflow of how the new discovery system has been redesigned from user requirements and how the data are distributed to the scientific community.

ACCESSING AND PROCESSING BRAZILIAN EARTH OBSERVATION DATA CUBES WITH THE OPEN DATA CUBE PLATFORM

Abstract. Recently, several technologies have emerged to address the need to process and analyze large volumes of Earth Observations (EO) data. The concept of Earth Observations Data Cubes (EODC) appears, in this context, as the paradigm of technologies that aim to structure and facilitate the way users handle this type of data. Some projects have adopted this concept in developing their technologies, such as the Open Data Cube (ODC) framework and the Brazil Data Cube (BDC) platform, which provide open-source tools capable of managing, processing, analyzing, and disseminating EO data. This work presents an approach to integrate these technologies through the access and processing of data products from the BDC platform in the ODC framework. For this, we developed a tool to automate the process of searching, converting, and indexing data between these two systems. Besides, four ODC functional modules have been customized to work with BDC data. The tool developed and the changes made to the ODC modules expand the potential for other initiatives to take advantage of the features available in the ODC.

Revealing students’ stories as they construct and use a statistical model in TinkerPlots to conduct a randomization test for comparing two groups

ABSTRACT Using simulation approaches when conducting randomization tests for comparing two groups in the context of experimental studies has been promoted as a beneficial approach for supporting student learning of statistical inference. Many researchers have suggested that the data production process in simulations for the randomization test intuitively connects to the random assignment used in the original study design, thus supporting students’ understanding of the logic of inference. Yet, there is little empirical research on how students initially think about the concepts and processes underlying the randomization test as they engage in constructing and using probability models to solve a problem. This work makes a contribution by deepening our understanding of students’ reasoning about randomization tests by focusing on a group of three students as they create and use a TinkerPlots model to simulate data and use this data to make a statistical inference. This work adopts a narrative lens through which to view these students’ reasoning and modeling activity. We compare and contrast the narratives we constructed for these students along with a narrative we constructed for a statistician. We discuss possible implications for teaching randomization tests for comparing two groups using a modeling and simulation approach.

The EMIT mission information yield for mineral dust radiative forcing

The net direct radiative effect of mineral dust is a large uncertainty in global radiative forcing. To address this challenge, NASA's Earth Mineral dust source InvesTigation (EMIT) will map the surface mineralogy of Earth's desert dust source regions, constraining the composition of mineral dust aerosol for use in Earth system models (ESMs). This mission foreshadows multiple future global spectroscopic investigations for which coupling with ESMs will play a critical role. Planning such experiments requires a methodology for assessing the impact of uncertain remote observations on ESM accuracy. We design and implement an end-to-end simulation of the EMIT mission, leveraging Bayesian statistical methods and Monte Carlo sampling to analyze uncertainties in the retrieval and processing of EMIT data products. Special focus is placed on those uncertainties caused by atmospheric water vapor and aerosol loading conditions likely to be encountered by EMIT. We apply these results to a single-column configuration of the Community Earth System Model (CESM), revealing the potential impact of EMIT observations on radiative forcing estimates. We show that EMIT data stand to significantly reduce uncertainty in estimates of the dust direct radiative forcing attributable to uncertainties in surface mineralogies that are input to ESMs, and that the information gain for radiative forcing comes predominantly from better constraining iron oxides, which dominate the shortwave radiative effects of aerosol dust.

ParlTech: Transformation Framework for the Digital Parliament

Societies are entering the age of technological disruption, which also impacts governance institutions such as parliamentary organizations. Thus, parliaments need to adjust swiftly by incorporating innovative methods into their organizational culture and novel technologies into their working procedures. Inter-Parliamentary Union World e-Parliament Reports capture digital transformation trends towards open data production, standardized and knowledge-driven business processes, and the implementation of inclusive and participatory schemes. Nevertheless, there is still a limited consensus on how these trends will materialize into specific tools, products, and services, with added value for parliamentary and societal stakeholders. This article outlines the rapid evolution of the digital parliament from the user perspective. In doing so, it describes a transformational framework based on the evaluation of empirical data by an expert survey of parliamentarians and parliamentary administrators. Basic sets of tools and technologies that are perceived as vital for future parliamentary use by intra-parliamentary stakeholders, such as systems and processes for information and knowledge sharing, are analyzed. Moreover, boundary conditions for development and implementation of parliamentary technologies are set and highlighted. Concluding recommendations regarding the expected investments, interdisciplinary research, and cross-sector collaboration within the defined framework are presented.

On adequacy of parameters of strip cross-section profile. Part 1. Predictive interval

Increasing the level of automation of metallurgical units and the development of industrial information systems increases the number of p ters of production and technological processes available for analysis. The consequence is an increase in the complexity and duration of preliminary data preparation for subsequent mathematical and statistical analysis. It is therefore important to develop new and improve existing techniques for the automated process of primary data production. When developing methods of primary data preparation, it should be taken into account that accuracy and adequacy of results of subsequent mathematical analysis are determined by accuracy and adequacy of used initial data. The cross-sectional profile parameters of hot-rolled strips, such as wedge, convexity, thickness variation, displacement, wedge in near-rim zones, local thickenings and thinning of the strip are calculated parameters, i.e. secondary to actual strip thickness measurements over the length and width of hot-rolled strips. As technology is improved in cold rolling shops, the number of grade groups is increasing, for which technological modes of units and processing routes are selected. They are based on actual values of parameters of cross-section profile in order to further reduce the probability of formation of inappropriate products and increased metal consumption. The presented article provides an overview of conventional calculation methods for parameters of cross-section profile of hot-rolled strip and gives an assessment of accuracy and adequacy of application of the parameters averaged along strip length to the whole strip.

Assessing the spatial accuracy of UAV-derived products based on variation of flight altitudes

Unmanned Aerial Vehicles (UAVs), which can carry a variety of payloads, and be operated automatically or manually with ground control stations. Nowadays, UAVs can make photogrammetric flight plans and obtain photogrammetric data with existing sensor systems. Automatic data acquisition processes provide lower cost, and high spatial and temporal resolution images in a short period of time compared to other measurement methods. As a result, orthomosaics, dense point clouds and digital surface models (DSMs) are produced and these UAV-derived data are used in various disciplines such as constructions, geomatics, earth sciences, etc. In this study, the same flight plans were realized with an UAV at different altitudes and all aerial images were obtained with the same integrated digital camera. As a result of the processing of images acquired from different altitudes, orthomosaics, DSMs and point cloud were produced. In this study, it is aimed to compare the length, areal and volumetric differences of a small geostationary object. Ground control points (GCPs), which were collected by RTK-GPS (Real-Time Kinematic) in conjunction with the flight integrated into data production process in order to highly accurate product. Ultimately, cross-correlation has been done with the produced data and the terrestrial measurement. Results show that the dimension of the object depend on the flight altitude as expected, however the volumetric changes vary due to the uncertainties in the raw point cloud data.

RIGHT TO THE MAP? COUNTER-MAPPING PRACTICES OF SMOG ALERTS AND URBAN GREENERY MOVEMENTS IN POLAND

Data production is becoming an emerging trend in critical urban activism. Precise and reliable public information, including spatial and environmental information, serves individual and collective ‘right to the city’ beliefs. One of the common strategies adopted by contemporary urban movements to ensure the accuracy and inclusiveness of urban data production processes are various forms of counter-mapping, which we introduce in this paper as a perspective aimed in critical evaluation of urban environmental conditions in Polish cities. By process tracing of smog alerts and urban greenery movements, we investigate the main strategies of using such tools and their effects for both particular social actors, and general urban environmental policy. We argue that the core idea of a citizen-driven collection of geographical data is strongly supported by its other features – social involvement and collective production of visualizations illustrating the scale and dynamics of particular environmental problems. In this sense, counter-mapping is aimed rather at repoliticizing urban environmental data in order to critically evaluate existing urban policy, than just to ensure greater citizen involvement in environmental decision-making.

Accuracy assessments of Göktürk-1 satellite imagery

Optical satellite imagery has an important place today in terms of responding to the increasing need for geospatial base in many different fields and disciplines, especially because of their availability and temporal resolution. Because all kinds of geospatial information and data production processes such as orthoimages, maps, vector data and etc. in especially for large project areas provide the opportunity to reduce the cost and time required in the field work, so the interest in high resolution satellite imagery. Göktürk-1, an electro-optical satellite that was launched on December 5, 2016 and acquiring 0.50 m spatial resolution imagery, aims to meet the high resolution image requirements of Turkey. In this study, the horizontal and vertical accuracy of the Digital Surface Model and orthoimages produced by different methods from stereo images obtained from Göktürk-1 satellite in two different regions were investigated. As a result, although the pointing accuracy and the Digital Surface Model accuracy produced from Göktürk-1 satellite imagery, will vary according to the incidence angle of Göktürk-1 satellite, the Digital Terrain Model used in the production of the orthoimage, the selected method for orientation of satellite imagery; a planimetric accuracy of better than ± 2 m RMSE in orthoimage and a height accuracy of better than ± 3 m RMSE is accomplished.

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.

Leveraging Administrative Data for Policy and Programmatic Interventions on Gender Specific Sustainable Development Goals (SDGs)

Leveraging Administrative Data for Policy and Programmatic Interventions on Gender Specific Sustainable Development Goals (SDGs)

Corpo e escola: o que o brincar nas filas [re]vela

Neste trabalho tivemos como objetivo investigar o brincar nas filas de uma Escola de Tempo Integral da prefeitura Municipal de Campinas. Para tanto, realizamos uma pesquisa de cunho qualitativo interpretativo, observando uma turma de 1º ano do ciclo I do Ensino Fundamental, durante um semestre. Utilizamos diário de campo e escrevemos narrativas sobre as observações no processo de produção dos dados. Chamamos atenção principalmente para as estratégias de controle dos corpos e expressões utilizadas pelas professoras, assim como, para o brincar transgressor e resistente, que rompia com a continuidade na dinâmica da cultura escolar, subvertendo ou pelo menos revelando que outra escola seria possível de existir, com outras normas, outras configurações, outras regras, outros sentidos e significações.

Psychology: a Discipline in Need of Reflective Foundations.

Zagaria, Andó and Zennaro (2020) provide a useful analysis of the current state of affairs in the discipline of psychology. They conclude that psychology is in a messy and unproductive pre-pragmatic state and suggest that evolutionary psychology can provide a needed metatheoretical perspective to enable psychology to move forward as a science. In my commentary I move to another direction and suggest that psychology does not need more solid foundations, but rather foundations characterized by reflective stance towards its phenomena, theories, methods and data production processes. I suggest that this kind of stance would be in accordance with the process ontological perspective that allows focusing on meaningful human experience as central object of study for psychology, together with an idiographic approach to research. I thus suggest that psychology will endure only by turning its reflective gaze towards oneself, by thinking about its past, imagining its future and constructing novelty from the creative assemblage of the two.

Issues in Tourism Statistics: A Critical Review

The purpose of this paper is a discussion of some major concepts and operational definitions involved in tourism statistics within Regulation 692/2011, with a cross-country comparison and an in-depth look at the Italian case. Data and information are derived from main documents of major international and national institutions and Eurostat metadata. Both demand-side and supply-side data sources on tourism are discussed. The work highlights the main differences in the data production processes of different EU countries, although they follow the same regulation. The main critical points are: the definition of usual environment and survey design for the demand-side data, as well as the statistical unit for the supply-side data, which does not coincide with that used in structural business statistics. The analysis is limited to those EU countries with complete available Eurostat metadata. Moreover, only household surveys relating to trips and vacations are considered for demand-side data (border surveys are not treated). The main contribution is concerned with the description of the current situation in the production of tourism statistics, by looking and their comparability for cross-country analyses and at the possibility of their integration and reconciliation in the perspective of building a system of tourism statistics.

Interdisciplinaridade e estatística nos dados de escravos sepultados em Porto Alegre (1850-1885)

Este artigo apresenta resultados de uma pesquisa de um mestrado profissional no campo da Educação Estatística feita com estudantes do 7º ano em uma escola privada de Canoas-RS. A questão A busca pela compreensão de dados demográficos dos escravos sepultados no cemitério da Santa Casa de Porto Alegre, no século XIX, pode contribuir no aprendizado de Estatística? serviu para um projeto interdisciplinar de Matemática, História e Ciências. Com uma amostra aleatória de 1559 registros de óbitos dos escravos constantes no livro “Africanos na Santa Casa de Porto Alegre: Óbitos dos escravos sepultados no cemitério da Santa Casa (1850 a 1885)”, a turma fez gráficos e tabelas. Através de pré e pós testes se avaliou que houve avanços no aprendizado de conceitos estatísticos. Conceitos estatísticos foram mobilizados nas atividades e o olhar interdisciplinar favoreceu o processo de produção e análise dos dados, bem como fomentou o debate sobre a escravidão negra em Porto Alegre no século XIX.

Increasing the maturity of measurements of essential climate variables (ECVs) at Italian atmospheric WMO/GAW observatories by implementing automated data elaboration chains

In the framework of the National Project of Interest NextData, we developed automatic procedures for the flagging and formatting of trace gases, atmospheric aerosols and meteorological data to be submitted to the World Data Centers (WDCs) of the Global Atmosphere Watch program of the World Meteorological Organization (WMO/GAW). In particular, the atmospheric Essential Climate Variables (ECVs) covered in this work are observations of near-surface trace gas concentrations, aerosol properties and meteorological variables, which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG), the World Data Center for Reactive Gases, and the World Data Center for Aerosol (WDCRG and WDCA). We developed an overarching processing chain to create a number of data products (data files and reports) starting from the raw data, finally contributing to increase the maturity of these measurements. To this aim, we implemented specific routines for data filtering, flagging, format harmonization, and creation of data products, useful for detecting instrumental problems, particular atmospheric events and quick data dissemination towards stakeholders or citizens. Currently, the automatic data processing is active for a subset of ECVs at 5 measurement sites in Italy. The system represents a valuable tool to facilitate data originators towards a more efficient data production. Our effort is expected to accelerate the process of data submission to WMO/GAW or to other reference data centers or repositories. Moreover, the adoption of automatic procedures for data flagging and data correction allows to keep track of the process that led to the final validated data, and makes data evaluation and revisions more efficient by improving the traceability of the data production process.