In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 60, Heft 9, S. 23-29
The article highlights the need to broaden the analysis of the quality of the survey results, taking into account the negative impact of certain operations of so-called editing input data, such as checking their accuracy and correction of errors. In the conclusions it underlines the need to extend the programs for academic lectures in statistics for analysis of the impact of processing operations on the quality of the results.
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Data analyses using methods of exploratory and inductive statistics nowadays form an integral part of many areas of human activities. The paper is focused on the statistical processing of data using a new application STAT1 that works under Microsoft Office Excel. The explanation is given, the source is stated, and the comparison with alternative application software tools is mentioned. Moreover, the examples of practical utilization of STAT1 in the military area are presented.
Governments across the world are intensifying their use of digital technology. One way to generate an understanding of the effects of technology in the public sector is to study values. The purpose of this paper is to investigate how values in the Swedish national e-Government have developed over time. This research studies Swedish government documents between 1961 and 2018 during three periods of computerization: Automatic Data Processing, Information Technology, and Digitalization. A theoretical framework that consists of four value positions (i.e. professionalism, efficiency, service, and engagement) is utilized. The findings suggest that technological paradigms tend to generate value congruence in policy documents, followed by value divergence in evaluations. Currently, digitalization is perceived as the enabler of several values. While both IT and digitalization are referred to as tools or means, the development towards an information, knowledge, or data-driven society is also described as inevitable. The service ideal became dominant through the use of internet-based technology, while efficiency is often prioritized in large-scale projects. Engagement values are associated with a futuristic form of democracy in government documents, but rarely converted into practice. The role of professionalism is two-fold: it acts both as an enabler and as a constraint to the other values. The paper concludes with suggesting that the current development of adapting laws and regulations to enable digitalization might lead to an eroded bureaucracy, with uncertain value.
CEI (Ciudad Energéticamente Inteligente – Energetically Smart City) aims at improving the energy and environment conditions of living areas of the city, by managing correctly the existing infrastructures and resources. The improvement will be enabled by the development of technology systems (energy nodes control technologies, energy-environmental sensors technologies, technologies for the improvement of maintenance methodologies) that make possible the control of energy and environment conditions of those areas. This project is funded by the Instituto Valenciano de Competitividad Empresarial (IVACE) and the European Union through the Fondo Europeo de Desarrollo Regional (FEDER). This work package aims at designing and developing the ICT system associated to the energy management systems considered in the project. The first layer of this architecture tackles data acquisition: energy data, weather data, and other relevant data from the energy management systems deployed in the city. After data collection, the system implements two analysis modules: · A rule-based correlation engine, which will identify events over a subset of data sources. · A big data analytics engine, which will learn from historical data by applying statistical techniques. This document describes the components of the Big Data Analytics platform, focusing on the data processing and analysis (both statistical and rule-based). Finally, a front-end web shows the information handled by the platform. ; CEI (Ciudad Energéticamente Inteligente – Energetically Smart City). Project funded by the Valencian Institute of Business Competitiveness (IVACE) and European Union through the European Regional Development Fund (ERDF), within the public grant program adressed to Technological Institutes of the Valencian Community for 2016. File number: IMDECB/2016/60
Abstract This paper presents the data processing methodology for the physical modeling of ocean waves in wave flumes which was developed for the purpose of conducting hydrodynamics research in laboratory conditions. It includes the description of the research cycle, applied wave theory and the measured data processing methods. A significant achievement presented in this paper is the originally developed data analysis algorithm for the practical improvement of the wave generation process.