scholarly journals A Study on Data Profiling: Focusing on Attribute Value Quality Index

2019 ◽  
Vol 9 (23) ◽  
pp. 5054
Author(s):  
Jang ◽  
Lee ◽  
Kim ◽  
Gim
Keyword(s):  
Data Quality ◽  
Quality Index ◽  
Industrial Revolution ◽  
Calculation Model ◽  
Point Of View ◽  
Quality Data ◽  
Digital Information ◽  
Core Technology ◽  
High Level ◽  
Attribute Value

In the era of the Fourth Industrial Revolution, companies are focusing on securing artificial intelligence (AI) technology to enhance their competitiveness via machine learning, which is the core technology of AI, and to allow computers to acquire a high level of quality data through self-learning. Securing good-quality big data is becoming a very important asset for companies to enhance their competitiveness. The volume of digital information is expected to grow rapidly around the world, reaching 90 zettabytes (ZB) by 2020. It is very meaningful to present the value quality index on each data attribute as it may be desirable to evaluate the data quality for a user with regard to whether the data is suitable for use from the user’s point of view. As a result, this allows the user to determine whether they would take the data or not based on the data quality index. In this study, we propose a quality index calculation model with structured and unstructured data, as well as a calculation method for the attribute value quality index (AVQI) and the structured data value quality index (SDVQI).

scholarly journals THE SLOVAK CITIZEN’S AND UNIVERSITY STUDENT’S PERSPECTIVE ON THE BENEFITS OF ROBOTIZATION

2019 ◽  
Vol 7 ◽  
Author(s):  
Tomáš Mišík ◽  
Jana Štofková
Keyword(s):  
Industrial Revolution ◽  
New Technologies ◽  
Technological Development ◽  
Theoretical Background ◽  
Point Of View ◽  
Skills Acquisition ◽  
Employment Policy ◽  
Job Opportunities ◽  
Education And Employment ◽  
High Level

We live in a time which is determined by rapid technological development, increasing automation, creating electronic services and implementing robots. The current Fourth Industrial Revolution is not just about technology or business, it is also about society, the quality of life and the integration of new technologies where humans and robots interact. New technologies create space for job opportunities that will require specific kinds of skills. Today, computers and machines can do a high level of work involving routine and manual work, but they cannot replace some analytical, creative and, most importantly, social skills. An education and employment policy is needed to transform the trends and challenges of the digital economy. The aim of the contribution is point to the theoretical background of the digital transformation of society and define the level of robot skills acquisition. Moreover, it identifies the life situations and sectors where respondents from Slovakia would accept the presence of robots and the article compares data with a survey conducted by 168 students of Zilina university. The contribution also focuses attention on the approach to the relationship between human and the robot and the perceived benefits of using robots from the point of view of citizens.

PDQ (Product Data Quality): Representation of Data Quality for Product Data and Specifically for Shape Data

2010 ◽  
Vol 10 (2) ◽  
Author(s):  
Yoshihito Kikuchi ◽  
Hiroyuki Hiraoka ◽  
Akihiko Otaka ◽  
Fumiki Tanaka ◽  
Kazuya G. Kobayashi ◽  
...  
Keyword(s):  
Data Quality ◽  
Manufacturing Process ◽  
Point Of View ◽  
International Standard Organization ◽  
Quality Data ◽  
Model Data ◽  
Product Model ◽  
Product Data ◽  
Iso 10303 ◽  
Shape Data

In the communication and sharing of product data, if the difference of the required data quality and the data quality actually incorporated into data is significant, it causes various problems. It is often the case that a creator of low quality data does not realize it unless it is harmful for his job. In most cases, low quality data passed to subsequent processes, such as manufacturing process, cause problems since these are not appropriate from the machining precision point of view or the detailed shape modeling point of view. In these cases, rework or repair of data is necessitated before commencing the target process, which results in significant economy loss and delay of product development. Today’s product model data are dumb data because design intents and data quality incorporated are not explicitly represented. Receiving systems cannot know whether the data passed possess sufficient quality for the target job or not. Another problem is that engineers in later processes, such as the manufacturing process, cannot issue data quality related request beforehand in a commonly agreed manner. The problems mentioned above are caused by the lack of a commonly agreed representation of product data quality (PDQ) information. Our proposed solution is designed to enable the communication and sharing of data quality information. This paper reports the development of a PDQ standard (ISO 10303-59), which is a resource part of ISO 10303 Standard for the Exchange of Product Model Data (STEP) (2008, “ISO 10303-59, Industrial Automation Systems and Integration. Product Data Representation and Exchange. Part 59 Integrated Generic Resource: Quality of Product Shape Data,” International Standard Organization, Geneva). The objective of ISO 10303-59 is to establish a PDQ model and to enable the use of PDQ data independently or in combination with product data. The developed PDQ information model represents concepts such as data quality criteria, measurement requirements, and measured results. Based on the PDQ model, the PDQ for shape data model, which is a specialization of the PDQ model to 3D shape data quality, is also developed.

scholarly journals Challenges in Data Quality and Complexity of Managing Data Quality Assessment in Big Data

2020 ◽  
Vol 9 (3) ◽  
pp. 589-593
Keyword(s):  
Data Quality ◽  
Large Data ◽  
Point Of View ◽  
Quality Data ◽  
Quality Information ◽  
High Quality ◽  
High Quality Data ◽  
Equal Time ◽  
The Troubles ◽  
Data Quality Assessment

High Quality Data are the precondition for examining and making use of enormous facts and for making sure the estimation of the facts. As of now, far reaching exam and research of price gauges and satisfactory appraisal strategies for massive records are inadequate. To begin with, this paper abridges audits of Data excellent studies. Second, this paper examines the records attributes of the enormous records condition, presents high-quality difficulties appeared by large data, and defines a progressive facts exceptional shape from the point of view of records clients. This system accommodates of big records best measurements, best attributes, and best files. At long last, primarily based on this system, this paper builds a dynamic appraisal technique for records exceptional. This technique has excellent expansibility and versatility and can address the troubles of enormous facts fine appraisal. A few explores have verified that preserving up the character of statistics is regularly recognized as hazardous, however at the equal time is considered as simple to effective basic leadership in building aid the executives. Enormous data sources are exceptionally wide and statistics structures are thoughts boggling. The facts got may additionally have satisfactory troubles, for example, facts mistakes, lacking data, irregularities, commotion, and so forth. The motivation behind facts cleansing (facts scouring) is to pick out and expel mistakes and irregularities from facts so as to decorate their quality. Information cleansing may be separated into 4 examples dependent on usage techniques and degrees manual execution, composing of splendid software programs, records cleaning inconsequential to specific software fields, and taking care of the difficulty of a kind of explicit software area. In these 4 methodologies, the 1/3 has terrific down to earth esteem and may be connected effectively.

What Can Digitization Do For Formulated Product Innovation and Development

2020 ◽  
Author(s):  
James McDonagh ◽  
William Swope ◽  
Richard L. Anderson ◽  
Michael Johnston ◽  
David J. Bray
Keyword(s):  
High Performance ◽  
Quality Data ◽  
High Quality Data ◽  
Base Level ◽  
Hybrid Approaches ◽  
Digital Ecosystem ◽  
Recent Developments ◽  
Chemical Simulation ◽  
High Level ◽  
Physical And Chemical

Digitization offers significant opportunities for the formulated product industry to transform the way it works and develop new methods of business. R&D is one area of operation that is challenging to take advantage of these technologies due to its high level of domain specialisation and creativity but the benefits could be significant. Recent developments of base level technologies such as artificial intelligence (AI)/machine learning (ML), robotics and high performance computing (HPC), to name a few, present disruptive and transformative technologies which could offer new insights, discovery methods and enhanced chemical control when combined in a digital ecosystem of connectivity, distributive services and decentralisation. At the fundamental level, research in these technologies has shown that new physical and chemical insights can be gained, which in turn can augment experimental R&D approaches through physics-based chemical simulation, data driven models and hybrid approaches. In all of these cases, high quality data is required to build and validate models in addition to the skills and expertise to exploit such methods. In this article we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. We discuss the challenges in building and deploying these demonstrators.<br>

Designing Information Product (IP) Maps On the Process of Data Processing and Academic Information

2017 ◽  
Vol 4 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Diana Effendi
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Management ◽  
Information Quality ◽  
Quality Data ◽  
Management Approach ◽  
Quality Of Data ◽  
Information Product ◽  
Academic Activities

Information Product Approach (IP Approach) is an information management approach. It can be used to manage product information and data quality analysis. IP-Map can be used by organizations to facilitate the management of knowledge in collecting, storing, maintaining, and using the data in an organized. The  process of data management of academic activities in X University has not yet used the IP approach. X University has not given attention to the management of information quality of its. During this time X University just concern to system applications used to support the automation of data management in the process of academic activities. IP-Map that made in this paper can be used as a basis for analyzing the quality of data and information. By the IP-MAP, X University is expected to know which parts of the process that need improvement in the quality of data and information management.   Index term: IP Approach, IP-Map, information quality, data quality. REFERENCES[1] H. Zhu, S. Madnick, Y. Lee, and R. Wang, “Data and Information Quality Research: Its Evolution and Future,” Working Paper, MIT, USA, 2012.[2] Lee, Yang W; at al, Journey To Data Quality, MIT Press: Cambridge, 2006.[3] L. Al-Hakim, Information Quality Management: Theory and Applications. Idea Group Inc (IGI), 2007.[4] “Access : A semiotic information quality framework: development and comparative analysis : Journal ofInformation Technology.” [Online]. Available: http://www.palgravejournals.com/jit/journal/v20/n2/full/2000038a.html. [Accessed: 18-Sep-2015].[5] Effendi, Diana, Pengukuran Dan Perbaikan Kualitas Data Dan Informasi Di Perguruan Tinggi MenggunakanCALDEA Dan EVAMECAL (Studi Kasus X University), Proceeding Seminar Nasional RESASTEK, 2012, pp.TIG.1-TI-G.6.

Territorial Distribution of Alcohol and Drug Addictions Mortality Concerning Regional Disparities in the Slovak Republic from Year 1996 to Year 2015

2020 ◽  
Keyword(s):  
Mortality Rate ◽  
Slovak Republic ◽  
Regional Disparities ◽  
Point Of View ◽  
Extreme Position ◽  
Data Set ◽  
Female Sex ◽  
Male Sex ◽  
The Individual ◽  
High Level

BACKGROUND: This paper deals with territorial distribution of the alcohol and drug addictions mortality at a level of the districts of the Slovak Republic. AIM: The aim of the paper is to explore the relations within the administrative territorial division of the Slovak Republic, that is, between the individual districts and hence, to reveal possibly hidden relation in alcohol and drug mortality. METHODS: The analysis is divided and executed into the two fragments – one belongs to the female sex, the other one belongs to the male sex. The standardised mortality rate is computed according to a sequence of the mathematical relations. The Euclidean distance is employed to compute the similarity within each pair of a whole data set. The cluster analysis examines is performed. The clusters are created by means of the mutual distances of the districts. The data is collected from the database of the Statistical Office of the Slovak Republic for all the districts of the Slovak Republic. The covered time span begins in the year 1996 and ends in the year 2015. RESULTS: The most substantial point is that the Slovak Republic possesses the regional disparities in a field of mortality expressed by the standardised mortality rate computed particularly for the diagnoses assigned to the alcohol and drug addictions at a considerably high level. However, the female sex and the male sex have the different outcome. The Bratislava III District keeps absolutely the most extreme position. It forms an own cluster for the both sexes too. The Topoľčany District bears a similar extreme position from a point of view of the male sex. All the Bratislava districts keep their mutual notable dissimilarity. Contrariwise, evaluation of a development of the regional disparities among the districts looks like notably heterogeneously. CONCLUSIONS: There are considerable regional discrepancies throughout the districts of the Slovak Republic. Hence, it is necessary to create a common platform how to proceed with the solution of this issue.

Industry 4.0 initiatives in EU countries: experience for Ukraine

2020 ◽  
pp. 65-70
Author(s):  
Nataliya Ryvak ◽  
Anna Kernytska
Keyword(s):  
Industry 4.0 ◽  
Business Models ◽  
Industrial Revolution ◽  
Successful Implementation ◽  
Industrial Complex ◽  
Interconnected System ◽  
Industrial Transformation ◽  
Eu Countries ◽  
European Experience ◽  
High Level

In this paper, digital technologies development was analyzed as the basis for the so-called “fourth industrial revolution” with the potential for the qualitative transformation of the Ukrainian economy based on EU countries’ experience. Industry 4.0 is a new control chain over the entire chain of creating value throughout the product lifecycle. When developing an economic policy, it is important to pay attention to Industry 4.0. It increases productivity, produces new, better, and individualized products, and implements new business models based on “undermining” innovations. A comparative analysis of national initiatives I4.0 with their characteristics according to the main dimensions, including funding, focus, direction, was conducted. Particular attention was paid to considering deterrents to the successful implementation and enforcement of the I4.0 initiative in European countries. The factors of successful implementation of I4.0 initiatives in the EU countries were analyzed. Drawing on the analysis of the European experience of digital transformations in industry and national economies in general, the necessity of critical focus of such transformations in Ukraine was highlighted, and the need for state support of industrial transformation was substantiated. The emphasis was placed on the cooperation development between stakeholders within the implementation of Industry 4.0 – it is necessary to create national and regional 4.0 platforms, following the example of EU countries, which would bring together government institutions, businesses, and academics. The successful positioning of the Ukrainian modern industrial complex on the world markets depends on the high level of the interconnected system providing factors that characterize its development process. Considering the influence of a list of inhibiting factors on implementing the country’s industry accelerated development, a set of measures needed to transform Ukraine’s industry based on European experience was substantiated.

The Oxford Handbook of Sports Economics

2012 ◽  
Keyword(s):  
Economic Analysis ◽  
College Athletics ◽  
Team Sport ◽  
Antitrust Policy ◽  
Point Of View ◽  
Quality Data ◽  
Sports Economics ◽  
Managerial Behavior ◽  
The North ◽  
Individual Productivity

This book is the second volume of the two-volume The Oxford Handbook of the Economics of Sports which includes articles by nearly all of the important authors in the quickly growing field of sports economics. The two volumes consider in depth the ways that economics and sports interact with each other. To start with, economic analysis has helped with the understanding of many of the different institutions in sports. Secondly, quality data about individual productivity, salaries, career histories, teamwork, and managerial behavior has been useful in helping economists study topics as varied as the economics of discrimination, salary dispersion, and antitrust policy. The volumes are also rich from the point of view of the sports fan. Every major team sport is covered, and many interesting comparisons can be made especially between the North American League organization and the European-style promotion and relegation leagues. Golf, NASCAR, college athletics, women's sports, the Olympics, and even bowling are represented in these pages.

Arising of Informal Women's Learn-to-code Communities

2021 ◽  
Vol 21 (2) ◽  
pp. 1-24
Author(s):  
Louise Ann Lyon ◽  
Chelsea Clayton
Keyword(s):  
Learning Community ◽  
Virtual Communities ◽  
Point Of View ◽  
Customer Relationship ◽  
Activity System ◽  
Learning Group ◽  
Management Platform ◽  
High Level ◽  
Verbal Encouragement ◽  
Activity Systems Analysis

Female-focused, grassroots communities purporting to help women learn to code are popping up in a variety of settings, indicating the motivation on the part of the participants to evade male-dominated settings while learning. However, little is known about how these groups function as an activity system. With current technology enabling the forming of virtual communities and the meteoric rise in use of the Salesforce CRM (customer relationship management) platform, a group of women have formed a coaching and learning community designed to help women move from Salesforce administrators to software developers through learning to code. We used activity systems analysis (ASA) to investigate this real-world instance of the larger phenomenon using an ethnographic approach. We used ASA to organize and make sense of the data by first creating a table listing the points on the activity system triangle (subject, rules, object, etc.) and filling in the points of the triangle based on the design of the coaching and learning group as described by participants; this gave us a high-level view of the activity system. To understand the subjects’ point of view of the system, we then created a new column in the table to fill in themes that emerged from our qualitative data analysis organized by dimension of the activity system. This process enabled us to capture the activity and the voices of participants as well as tensions that had emerged in the system. Findings show a range of outcomes, from participants crediting the group as a kickstart to the journey to successfully landing a job as a developer to members stalling in their progress after involvement. Results also show that purposeful tensions of welcoming novice questions and offering unsolicited verbal encouragement built into the activity system create a welcoming, safe environment for women learning to code.

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