Models of organizing research data storage and usage: basic principles, processes and implementation mechanisms

2019 ◽  
pp. 45-54
Author(s):  
Yu. I. Shokin ◽  
A. V. Yurchenko
Keyword(s):  
Data Storage ◽  
Scientific Data ◽  
Research Data ◽  
Research Management ◽  
Data Driven ◽  
Basic Principles ◽  
Central Focus ◽  
Urgent Task ◽  
Concept Classes ◽  
Effective Use

Introduction: Storage and usage of research data become more sophisticated as their quantity and diversity grow. Research data have a number of features which do not allow you to copy the approaches and tools used in commercial or governmental data-processing facilities. Providing researchers with specialized tools for working with data is an urgent task in research management.Purpose: Identifying and describing the basic principles for working with research data, the processes and stages of this work, the mechanisms for implementing the principles and solving the problems of organizing the storage and usage of research data.Results: We review and discuss the principles on which the storage and usage of research data can be based, including the FAIR Data Principles. The main goal of organizing the work with research data and the central focus of its principles is the effective use and reuse of this data. We present a hierarchy of mechanisms which can be applied when working with research data for solving scientific and organizational problems. The main processes and lifecycle stages of scientific data and research processes based on them are listed in the article. A number of well-known models of such lifecycles are considered. It is proposed, instead of trying to build a universal model, to use or create models based on the presented list of stages for specific cases or classes of data-driven research.Practical relevance: The hierarchy of concept classes developed in the work for the field “Organizing the storage and usage of scientific data” will be used as an ontology core, and for the development of regulatory documents, recommendations and information systems supporting data-driven research.

Scientific data-driven evaluation of academic publications on environmental Kuznets curve

2021 ◽  
Vol 28 (14) ◽  
pp. 16982-16999
Author(s):  
Muhammad Farhan Bashir ◽  
Benjiang Ma ◽  
Muhammad Adnan Bashir ◽  
Bilal ◽  
Luqman Shahzad
Keyword(s):  
Environmental Kuznets Curve ◽  
Scientific Data ◽  
Data Driven ◽  
Kuznets Curve ◽  
Academic Publications

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

AI Assisted High Fidelity Multi-Physics Digital Twin of Industrial Gas Turbines

2021 ◽  
Author(s):  
Senthil Krishnababu ◽  
Omar Valero ◽  
Roger Wells
Keyword(s):  
Gas Turbine ◽  
Data Storage ◽  
Gas Turbines ◽  
Building Blocks ◽  
Data Driven ◽  
High Fidelity ◽  
Test Field ◽  
Operating Characteristics ◽  
Digital Twin ◽  
The Impact

Abstract Data driven technologies are revolutionising the engineering sector by providing new ways of performing day to day tasks through the life cycle of a product as it progresses through manufacture, to build, qualification test, field operation and maintenance. Significant increase in data transfer speeds combined with cost effective data storage, and ever-increasing computational power provide the building blocks that enable companies to adopt data driven technologies such as data analytics, IOT and machine learning. Improved business operational efficiency and more responsive customer support provide the incentives for business investment. Digital twins, that leverages these technologies in their various forms to converge physics and data driven models, are therefore being widely adopted. A high-fidelity multi-physics digital twin, HFDT, that digitally replicates a gas turbine as it is built based on part and build data using advanced component and assembly models is introduced. The HFDT, among other benefits enables data driven assessments to be carried out during manufacture and assembly for each turbine allowing these processes to be optimised and the impact of variability or process change to be readily evaluated. On delivery of the turbine and its associated HFDT to the service support team the HFDT supports the evaluation of in-service performance deteriorations, the impact of field interventions and repair and the changes in operating characteristics resulting from overhaul and turbine upgrade. Thus, creating a cradle to grave physics and data driven twin of the gas turbine asset. In this paper, one branch of HFDT using a power turbine module is firstly presented. This involves simultaneous modelling of gas path and solid using high fidelity CFD and FEA which converts the cold geometry to hot running conditions to assess the impact of various manufacturing and build variabilities. It is shown this process can be executed within reasonable time frames enabling creation of HFDT for each turbine during manufacture and assembly and for this to be transferred to the service team for deployment during field operations. Following this, it is shown how data driven technologies are used in conjunction with the HFDT to improve predictions of engine performance from early build information. The example shown, shows how a higher degree of confidence is achieved through the development of an artificial neural network of the compressor tip gap feature and its effect on overall compressor efficiency.

scholarly journals Tutkimusaineiston avoin jakaminen – tutkimusorganisaatioiden jäsenten käsityksiä, kokemuksia ja mielipiteitä

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Heidi Enwald
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Online Survey ◽  
Open Science ◽  
Research Data ◽  
Research Field ◽  
Open Research ◽  
Research Organizations ◽  
Data Collection Instrument ◽  
In The Beginning

Open research data is data that is free to access, reuse, and redistribute. This study focuses on the perceptions, opinions and experiences of staff and researchers of research institutes on topics related to open research data. Furthermore, the differences across gender, role in the research organization and research field were investigated. An international questionnaire survey, translated into Finnish and Swedish, was used as the data collection instrument. An online survey was distributed through an open science related network to Finnish research organizations. In the end, 469 responded to all 24 questions of the survey. Findings indicate that many are still unaware or uncertain about issues related to data sharing and long-term data storage. Women as well as staff and researchers of medical and health sciences were most concerned about the possible problems associated with data sharing. Those in the beginning of their scientific careers, hesitated about sharing their data.

scholarly journals Mediating Corporeality: Re-Interpretations at the Art/Science Interface

Somatechnics ◽  
2012 ◽  
Vol 2 (2) ◽  
pp. 284-304
Author(s):  
Patricia Adams
Keyword(s):  
Digital Imaging ◽  
Scientific Research ◽  
Digital Technologies ◽  
Adult Stem Cell ◽  
Image Data ◽  
Scientific Data ◽  
Research Data ◽  
The Self ◽  
First Century ◽  
Individual Perspective

Contemporary scientific discoveries are rapidly modifying established concepts of embodiment and corporeality. For example, developing techniques in adult stem cell research can actively remodel the human body; whilst neuroscientists are shedding increasing light on the functioning of our brains. My research at the art/science nexus draws upon recent media theories to investigate the ways twenty-first century constructs of ‘humanness’ and the ‘self’ are affected by both historical and contemporary scientific research and developments in digital imaging technologies. In this article, examples from my artworks: “machina carnis” and “HOST” illustrate how my use of innovative digital technologies and collaborative methodologies has enabled me to immerse myself in the scientific experience at first hand. I demonstrate how my reinterpretations of what is commonly termed ‘hard’ scientific research data does not seek to emulate ‘objective’ readings of the experimental digital image data but rather recontextualises it in the context of my artworks. These artworks acknowledge the personal and visceral content in the scientific data and enable viewer/participants to reflect upon the issues raised from an emotive and individual perspective.

scholarly journals Data Papers as a New Form of Knowledge Organization in the Field of Research Data

2019 ◽  
Vol 46 (8) ◽  
pp. 622-638
Author(s):  
Joachim Schöpfel ◽  
Dominic Farace ◽  
Hélène Prost ◽  
Antonella Zane
Keyword(s):  
Business Models ◽  
Open Science ◽  
Research Data ◽  
Data Driven ◽  
Academic Publishing ◽  
Science Data ◽  
Research Data Management ◽  
Fair Principles ◽  
New Form ◽  
Machine Readable

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.

Comparing mathematical and heuristic approaches for scientific data analysis

2007 ◽  
Vol 22 (1) ◽  
pp. 53-69 ◽  
Author(s):  
Aparna S. Varde ◽  
Shuhui Ma ◽  
Mohammed Maniruzzaman ◽  
David C. Brown ◽  
Elke A. Rundensteiner ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Data Storage ◽  
Materials Science ◽  
Scientific Data ◽  
Estimation Problem ◽  
Predictive Analysis ◽  
Heuristic Methods ◽  
Science Data ◽  
Domain Specific ◽  
Computational Estimation

AbstractScientific data is often analyzed in the context of domain-specific problems, for example, failure diagnostics, predictive analysis, and computational estimation. These problems can be solved using approaches such as mathematical models or heuristic methods. In this paper we compare a heuristic approach based on mining stored data with a mathematical approach based on applying state-of-the-art formulae to solve an estimation problem. The goal is to estimate results of scientific experiments given their input conditions. We present a comparative study based on sample space, time complexity, and data storage with respect to a real application in materials science. Performance evaluation with real materials science data is also presented, taking into account accuracy and efficiency. We find that both approaches have their pros and cons in computational estimation. Similar arguments can be applied to other scientific problems such as failure diagnostics and predictive analysis. In the estimation problem in this paper, heuristic methods outperform mathematical models.

scholarly journals PROBLEMS OF SPATIAL INTEGRATION OF RUSSIAN REGIONS

2021 ◽  
Vol 230 (4) ◽  
pp. 339-345
Author(s):  
S.A. KOZHEVNIKOV ◽  
Keyword(s):  
State Policy ◽  
Russian Regions ◽  
Spatial Integration ◽  
Economic Space ◽  
Interregional Interaction ◽  
The North ◽  
Urgent Task ◽  
Its Regions ◽  
The Subject ◽  
Effective Use

The article is devoted to the study of the urgent task for modern Russia - to ensure the spatial integration of its regions. The paper examines the theoretical aspects of the subject, substantiates the need for the integration of the country's economic space along the "North-South" line. The key barriers to the development of spatial integration are identified and the priorities of state policy to ensure the unity of the country's economic space are substantiated, aimed at the effective use of the potential of interregional interaction.

THE ROLE OF THE SYSTEM OF PASTURE TERMS AND TOPONYMS OF SARYARKA IN DETERMINING LANDSCAPE FEATURES

2021 ◽  
Vol 101 (2) ◽  
pp. 52-62
Author(s):  
A.Ye. Yeginbayeva ◽  
◽  
K.T. Saparov ◽  
Z.K. Myrzalieva ◽  
M.A. Aralbekova ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Agricultural Production ◽  
Animal Husbandry ◽  
Land Resources ◽  
Natural Conditions ◽  
Cattle Breeding ◽  
Urgent Task ◽  
Key Issues ◽  
Effective Use

In market conditions, one of the key issues of management is the effective use of available natural resources. In agricultural production, these are the problems of using land resources. An urgent task is the rational use of pasture resources according to the seasons of the year for the management of pasture cattle breeding. The article considers the reflection in geographical names of pasture names and terms used in traditional animal husbandry, which provide important information about the features of the landscape. In addition, the regularities of the use of natural conditions by the ethnic group that inhabited this territory, the spatial distribution of pasture terms characteristic ofa particular landscape are determined.

USE OF INFORMATION TECHNOLOGIES IN THE DEVELOPMENT OF INNOVATIVE ACTIVITIES OF COMMERCIAL BANKS

2021 ◽  
Vol 4 (3) ◽  
pp. 22-31
Author(s):  
Jamshid Kiryigitov ◽  
Keyword(s):  
Commercial Banks ◽  
Information Technologies ◽  
Banking System ◽  
Digital Technologies ◽  
Developed Countries ◽  
Current Situation ◽  
Innovative Development ◽  
Urgent Task ◽  
Effective Use ◽  
Positive Results

In this article shown the activities and experience of commercial banks of developed countries are studied and prospects of using information technologies in the development of innovative activities in the system of our national commercial banks. At the same time, opinions were expressedabout the possibility of achieving positive results using digital technologies on the basis of developmentof innovative activities of banks of Uzbekistan. Proceeding from this urgent task, the article developed proposals and conclusions on the coverage of the importance of innovative development of banking activities, theoretical views of our homeland and foreign scientists on this and the analysis of the current situation on innovative development of the banking system, as well as on the wide use of information technologies in the innovative development of banks. The opportunities are highlighted for innovative development of the banking system with the effective use of digital technologies

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