scholarly journals Regional Development in the Age of Big Data

2018 ◽  
Vol 12 (1) ◽  
pp. 1-9
Author(s):  
József Jankó ◽  
György Szabó
Keyword(s):  
Big Data ◽  
Professional Practice ◽  
Spatial Planning ◽  
Landscape Architecture ◽  
Analytical Approach ◽  
Expert Knowledge ◽  
Value Added ◽  
Heterogeneous Data ◽  
Territorial Development ◽  
Related Data

Our paper presents a forward looking analytical approach to the territorial development in a region ofthe Transylvanian Plain situated in the vicinity of Cluj-Napoca, Romania. We outlined the development ofthis region with the means of landscape architecture supported by a comparable assessment. In the ageof Big Data we settled at creative usage of traditional analysis. We extracted yet undetected informationfrom a limited amount of available as yet loosely related data. The key feature of the employed model isthe ontological traceability of cause and effect. Although technology is available to collect enormous data,expert knowledge gained by education and professional practice cannot be overlooked. We demonstratethat this method of location based analysis is capable of delivering value added to established principlesof spatial planning in the age of trustworthy, large volume, heterogeneous data.

Big data quality framework: a holistic approach to continuous quality management

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ikbal Taleb ◽  
Mohamed Adel Serhani ◽  
Chafik Bouhaddioui ◽  
Rachida Dssouli
Keyword(s):  
Big Data ◽  
Quality Management ◽  
Data Quality ◽  
Value Added ◽  
Holistic Approach ◽  
Research Area ◽  
Heterogeneous Data ◽  
Data Generation ◽  
Continuous Quality ◽  
Quality Profile

AbstractBig Data is an essential research area for governments, institutions, and private agencies to support their analytics decisions. Big Data refers to all about data, how it is collected, processed, and analyzed to generate value-added data-driven insights and decisions. Degradation in Data Quality may result in unpredictable consequences. In this case, confidence and worthiness in the data and its source are lost. In the Big Data context, data characteristics, such as volume, multi-heterogeneous data sources, and fast data generation, increase the risk of quality degradation and require efficient mechanisms to check data worthiness. However, ensuring Big Data Quality (BDQ) is a very costly and time-consuming process, since excessive computing resources are required. Maintaining Quality through the Big Data lifecycle requires quality profiling and verification before its processing decision. A BDQ Management Framework for enhancing the pre-processing activities while strengthening data control is proposed. The proposed framework uses a new concept called Big Data Quality Profile. This concept captures quality outline, requirements, attributes, dimensions, scores, and rules. Using Big Data profiling and sampling components of the framework, a faster and efficient data quality estimation is initiated before and after an intermediate pre-processing phase. The exploratory profiling component of the framework plays an initial role in quality profiling; it uses a set of predefined quality metrics to evaluate important data quality dimensions. It generates quality rules by applying various pre-processing activities and their related functions. These rules mainly aim at the Data Quality Profile and result in quality scores for the selected quality attributes. The framework implementation and dataflow management across various quality management processes have been discussed, further some ongoing work on framework evaluation and deployment to support quality evaluation decisions conclude the paper.

Organizational Knowledge of Digital Economy in Transformation, in Big Data, and in Internet of Things

2021 ◽  
pp. 463-476
Author(s):  
Vardan Mkrttchian ◽  
Serge Chernyshenko
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Expert Knowledge ◽  
Value Added ◽  
Organizational Knowledge ◽  
Digital Economy ◽  
The Internet ◽  
Specific Product ◽  
Business Partners ◽  
Place Of Origin

This article discusses issues related to organizational knowledge of the digital economy as expert knowledge for intelligent solutions in Transformation, in Big Data, in the Internet of Things. Applying as expert knowledge for intelligent solutions is a new term that describes the planning, search, production, distribution, and delivery of Mkrttchian digital avatars from the place of origin to consumption. This is very different from traditional ones because they are associated with specific product expertise that is generated using electronic data distributed on the Internet between business partners and value-added service providers operating in the general digital economy paradigm using blockchain technologies. The article focuses on analyzing business relationships and this integration into sustainable management systems.

Waldpolitischer Jahresrückblick 2010 | Annual review of swiss forest policy 2010

2011 ◽  
Vol 162 (5) ◽  
pp. 137-145 ◽  
Author(s):  
Willi Zimmermann
Keyword(s):  
Spatial Planning ◽  
Forest Conservation ◽  
Forest Policy ◽  
Value Added ◽  
Political Agenda ◽  
Annual Review ◽  
Forest Law ◽  
One Step ◽  
Climate Convention ◽  
Article 5

In 2010, there were no major forest policy issues that attracted media attention. The year 2010 was rather marked by the preparation of decisions “offstage” and by recurring administrative implementation activities. The partial revision of the forest law, which has been launched, can be regarded as special, because it is not a routine affair: the Committee for the Environment, Spatial Planning and Energy of the Council of States decided to revise particularly article 7 (compensation for deforestation) and article 10 (assessing forest status) of the forest law, and thus loosen the strict regime for forest conservation. Concerning the sectoral policies related to forest, the parliament took the law on spatial planning (RPG) one step further towards its revision. With the proposed revision of the spatial planning law's article 5 (value-added charge) a forest policy relevant article is now up for discussion. Different forest relevant topics on the international political agenda were discussed during the two international conferences on biodiversity and climate convention just as during the treatment of the alpine and the landscape convention. Next year the discussions will presumably be about the future forest conservation policy.

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

Big Data and Big Data Analytics for Improved Healthcare Service and Management

2020 ◽  
Vol 8 (1) ◽  
pp. 13-51
Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Moutan Mukhopadhyay
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
Future Market ◽  
Data Generation ◽  
Related Data ◽  
Healthcare Data ◽  
Different Types

Like other fields, the healthcare sector has also been greatly impacted by big data. A huge volume of healthcare data and other related data are being continually generated from diverse sources. Tapping and analysing these data, suitably, would open up new avenues and opportunities for healthcare services. In view of that, this paper aims to present a systematic overview of big data and big data analytics, applicable to modern-day healthcare. Acknowledging the massive upsurge in healthcare data generation, various ‘V's, specific to healthcare big data, are identified. Different types of data analytics, applicable to healthcare, are discussed. Along with presenting the technological backbone of healthcare big data and analytics, the advantages and challenges of healthcare big data are meticulously explained. A brief report on the present and future market of healthcare big data and analytics is also presented. Besides, several applications and use cases are discussed with sufficient details.

Bibliometric analysis and critical review of the research on big data in the construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusheng Lu ◽  
Jiantong Zhang
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Bibliometric Analysis ◽  
Critical Review ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
The Body ◽  
Future Research ◽  
Temporal And Spatial Distribution ◽  
Content Type

PurposeThe digital revolution and the use of big data (BD) in particular has important applications in the construction industry. In construction, massive amounts of heterogeneous data need to be analyzed to improve onsite efficiency. This article presents a systematic review and identifies future research directions, presenting valuable conclusions derived from rigorous bibliometric tools. The results of this study may provide guidelines for construction engineering and global policymaking to change the current low-efficiency of construction sites.Design/methodology/approachThis study identifies research trends from 1,253 peer-reviewed papers, using general statistics, keyword co-occurrence analysis, critical review, and qualitative-bibliometric techniques in two rounds of search.FindingsThe number of studies in this area rapidly increased from 2012 to 2020. A significant number of publications originated in the UK, China, the US, and Australia, and the smallest number from one of these countries is more than twice the largest number in the remaining countries. Keyword co-occurrence is divided into three clusters: BD application scenarios, emerging technology in BD, and BD management. Currently developing approaches in BD analytics include machine learning, data mining, and heuristic-optimization algorithms such as graph convolutional, recurrent neural networks and natural language processes (NLP). Studies have focused on safety management, energy reduction, and cost prediction. Blockchain integrated with BD is a promising means of managing construction contracts.Research limitations/implicationsThe study of BD is in a stage of rapid development, and this bibliometric analysis is only a part of the necessary practical analysis.Practical implicationsNational policies, temporal and spatial distribution, BD flow are interpreted, and the results of this may provide guidelines for policymakers. Overall, this work may develop the body of knowledge, producing a reference point and identifying future development.Originality/valueTo our knowledge, this is the first bibliometric review of BD in the construction industry. This study can also benefit construction practitioners by providing them a focused perspective of BD for emerging practices in the construction industry.

Transpunerea Directivei PIF și evaziunea fiscală la TVA

2020 ◽  
Vol 2020 (2020) ◽  
pp. 9-24
Author(s):  
Ioana Maria COSTEA ◽  
Keyword(s):  
European Union ◽  
Criminal Law ◽  
Tax Evasion ◽  
Analytical Approach ◽  
Comparative Method ◽  
Value Added ◽  
Time Limit ◽  
The European Union ◽  
Financial Interests ◽  
Blind Spots

Our study proposes a two-step analysis of the concept of VAT fraud, a time limit represented by the adoption of Directive (EU) 2017/1371 of the European Parliament and of the Council of 5 July 2017 on the fight against fraud to the Union’s financial interests by means of criminal law. Through our analytical approach, which uses the comparative method meticulously under the auspices of the limited interpretation imposed by criminal law, specific hypotheses are revealed regarding the forms of tax evasion in the European Union framework for the operation of value added tax. Equally, the study seeks to identify the blind spots of national law and the directions for refining tax evasion legislation.

scholarly journals THE EASTERN VECTOR OF RUSSIAN ECONOMY — SUCCESS BASED ON THE SYNERGY OF INTERACTION AND INTERREGIONAL COOPERATION

2021 ◽  
Vol 230 (4) ◽  
pp. 90-102
Author(s):  
V.A. KRYUKOV ◽  
◽  
N.I. SUSLOV ◽  
M.A. YAGOLNITSER ◽  
◽  
...  
Keyword(s):  
Value Added ◽  
State Dependence ◽  
Market Forces ◽  
Territorial Development ◽  
Pilot Projects ◽  
Strategic Development ◽  
Russian Economy ◽  
Regulation Policy ◽  
Interregional Cooperation ◽  
Stimulation Of

The paper elaborates on the problems of territorial development of the East Russia’s economy in terms of a rational regulation policy on behalf of the state. Dependence on purely market forces often fails as this overlooks strategic development priorities. There is a need for a new model of development, which presumes stimulation of the internal demand through localization of supplies for projects and value-added chains. The concept of ‘major investment impulse’ involves main pilot projects capable of accelerating the region’s development.

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