Towards intelligent distributed computing : cell-oriented computing

Distributed computing systems are of huge importance in a number of recently established and future functions in computer science. For example, they are vital to banking applications, communication of electronic systems, air traffic control, manufacturing automation, biomedical operation works, space monitoring systems and robotics information systems. As the nature of computing comes to be increasingly directed towards intelligence and autonomy, intelligent computations will be the key for all future applications. Intelligent distributed computing will become the base for the growth of an innovative generation of intelligent distributed systems. Nowadays, research centres require the development of architectures of intelligent and collaborated systems; these systems must be capable of solving problems by themselves to save processing time and reduce costs. Building an intelligent style of distributed computing that controls the whole distributed system requires communications that must be based on a completely consistent system. The model of the ideal system to be adopted in building an intelligent distributed computing structure is the human body system, specifically the body’s cells. As an artificial and virtual simulation of the high degree of intelligence that controls the body’s cells, this chapter proposes a Cell-Oriented Computing model as a solution to accomplish the desired Intelligent Distributed Computing system

The Role of Business Intelligence in Shaping Management Practices

Purpose: The aim of this study is to elaborate how business intelligence shapes concrete managerial practices in a case company context. Theory: The theory of this research consists of three key frameworks which are business intelligence (BI), strategy-as-practice (SAP), and sociomateriality. As a combination these will provide a valid framework to observe changes in managerial practices in relation to business intelligence. The synthesis also provides a theoretical lens, through which is it is possible to easily view the empirical results in theoretical context. Methodology: The empirical part of this thesis includes a case study, for an unnamed large-scale production company. The material was gathered by conducting semi-structured interviews with managers from the case company. The data is analysed by using content analysis. Findings and contribution: Changes in managerial practices were identified in relation to business intelligence. First of key findings were that managers are analysing the data in more depth, due to the fact that business intelligence provides the initial analysis. Second change was that managers are looking the operations of the company through more comprehensive view and they examine the cross-department causations in more detail. Third identified change in managerial practises was that operative optimization has become more apparent, as business intelligence enables it with more level of detail than beforeTavoite: Tutkimuksessa tarkastellaan, miten business intelligence muovaa johtamisen käytänteitä. Teoria: Tutkimuksen teoria koostuu kolmesta pääkehyksestä, joita ovat business intelligence (BI), strategia käytäntönä (SAP) ja sosiomateriaalisuus. Näiden yhdistelmä tarjoaa validin synteesin, jonka avulla voidaan tarkastella johtamisen käytänteissä tapahtuvia muutoksia suhteessa business intelligencen hyödyntämiseen. Synteesi tarjoaa myös teoreettisen linssin, jonka läpi on mahdollista tarkastella empiirisen tutkimuksen tuloksia teoreettisessa kontekstissa. Metodologia: Tutkimus toteutettiin tapaustutkimuksena, jonka kohteena oli suuri tuotantoyritys. Tutkimuksen aineisto kerättiin semistrukturoitujen haastattelujen avulla ja aineiston analyysimenetelmänä käytettiin sisällönanalyysia. Löydökset ja kontribuutio: Tutkimuksessa havaittiin business intelligencen aiheuttavan joitakin muutoksia johtamisen käytäntöihin. Ensimmäinen löydös oli se, että johtajat analysoivat dataa syvällisemmin, sillä business intelligencellä on kyky tarjota ensianalyysi pohjaten raakadataan. Toinen havaittu muutos oli se, että johtajat tarkastelevat yrityksen toimintaa sekä osastojen välisiä vuorovaikutussuhteita syvällisemmin. Kolmas tunnistettu muutos johtamiskäytännöissä oli se, että operatiivinen optimointi on lisääntynyt, kun business intelligence mahdollistaa datan tarkkailun tarkemmalla tasolla kuin aikaisemmin

Estonian research 2019

Editorial Board: Professor Ülo Niinemets (Estonian Universtiy of Life Sciences), Professor Erkki Karo (Tallinn Technical University, TalTec), Professor Rainer Kattel (Tallinn Technical University, TalTec), Professor Richard Villems (Universtiy of Tartu)As a small country with scarce natural resources, Estonia’s development relies mainly on knowledgeable and entrepreneurial people. After regaining independence, we have reached a position where simple development factors have been exhausted and it is becoming increasingly clearer that for further socio-economic advancement, the potential of research and development must be used more effectively. What is this potential, how does Estonian research compare internationally, what are the major persisting and current problems in research and development? In this overview, these questions are discussed based on facts and figures. The last similar overview Estonian Research 2016 was well received. The data and analyses on Estonian research and development presented there were widely used in many subsequent analyses and contributed arguments to discussions regarding research policies. The main structure of the overview is similar to the previous one, consisting of two interrelated parts. The first part includes four comprehensive articles, the first two explore the resources needed for conducting scientific research: monetary resources on the one hand and human resources on the other hand. The next two articles describe the performance of Estonian research. The first focuses on publishing activity and the quality of scientific publications and the second on the socio-economic impact of research and the interrelations of research and society. The articles in the first part are compiled so that the principal data would be comparable to the information presented in the previous overview. This way, it is possible to build time-series in similar overviews in the future. The second part of the overview consists of short articles on the current topical research policy issues. Estonian Research 2019 and the figures together with data tables are available on the webpage of the Estonian Research Council. An editorial board of professors Ülo Niinemets, Erkki Karo, Rainer Kattel and Richard Villems from the Estonian University of Life Sciences, Tallinn University of Technology, and University of Tartu oversaw the compilation of this publication. Special thanks to Professor Jüri Allik and Kalmer Lauk from the University of Tartu for their willingness to contribute a paper in a very limited time. The staff of the Department of R&D Analysis, Estonian Research Council helped gathering material for the articles, much substantial assistance was provided by Tiina Pärson, Leading Analyst at Statistics Estonia. Many thanks to them and also to the authors of the articles and photographs used in this publication. I would also like to thank the Research Council’s Executive Director Karin Jaanson for her numerous recommendations. Kadri Raudvere, the editor of this publication, deserves a special mention for assisting the authors in collecting new data and motivating them in a delicate way when the writing deadlines started to close in. The overview includes the most recent data that was available at the time of compiling the publication (end of 2018). Since collecting and submitting statistical data at the state level often takes up to a year or sometimes even longer, some statistical data dates back to 2017 or an even earlier time. The data mostly derives from OECD databases, Eurostat, Statistics Estonia, Ministry of Education and Research, Universities Estonia, and Estonian Research Council. We hope that the content of this overview offers food for thought for researchers, policy makers, and all others interested in research, and that it will provide support for substantiated discussions on research and fact-based policy making. Andres Koppel, Director General of Estonian Research Counci

Die Qualität von Organisationen : ein kommunikationsbasierter Messansatz

The goal of this research is to develop an understanding of what causes organizations and information systems to be “good” with regard to communication and coordination. This study (1) gives a theoretical explanation of how the processes of organizational adaptation work and (2) what is required for establishing and measuring the goodness of an organization with regard to communication and coordination. By leveraging concepts from cybernetics and philosophy of language, particularly the theoretical conceptualization of information systems as social systems and language communities, this research arrives at new insights. After discussing related work from systems theory, organization theory, cybernetics, and philosophy of language, a theoretical conceptualization of information systems as language communities is adopted. This provides the foundation for two exploratory field studies. Then a formal theory for explaining the adaptation of organizations via language and communication is presented. This includes measures for the goodness of organizations with regard to communication and coordination. Finally, propositions stemming from the theoretical model are tested using multiple case studies in six information system development projects in the financial services industry.Zielsetzung der hier vorgestellten Forschung ist es, ein Verständnis für die Güte von Organisationen und Informationssystemen im Hinblick auf Kommunikation und Koordination zu entwickeln. Diese Studie gibt (1) eine theoretische Erklärung zur Funktionsweise organisatorischer Anpassungsprozesse und (2) Handlungsanleitungen zur Messung der Güte einer Organisation im Hinblick auf Kommunikation und Koordination. Dies geschieht durch die Nutzung von Konzepten der Kybernetik und der Sprachphilosophie, insbesondere der Formalisierung von Informationssystemen als soziale Systeme und Sprachgemeinschaften. Nach der Diskussion bestehender Ansätze in der Systemtheorie, der Organisationstheorie, der Kybernetik und der Sprachphilosophie wird die Konzeptualisierung von Informationssystemen als Sprachgemeinschaften übernommen. Diese bildet die Grundlage für zwei explorative Feldstudien. Im Anschluss wird eine Theorie zur Erklärung der Anpassung von Organisationen durch Sprache und Kommunikation vorgestellt. Dies beinhaltet Maße für die Güte von Organisationen im Hinblick auf Kommunikation und Koordination. Schließlich werden anhand dieses theoretischen Modells Hypothesen aufgestellt und in einer multiplen Fallstudie in sechs Informationssystementwicklungsprojekten in der Finanzdienstleistungsindustrie überprüft

Ontology Pattern-Based Data Integration

Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. This dissertation represents a study on how small, self-contained ontologies, called ontology design patterns, can be employed to provide semantic interoperability in a cross-repository data integration system. The idea of this so-called ontology pattern- based data integration is that a collection of ontology design patterns can act as the global schema that still contains sufficient semantics, but is also flexible and simple enough to be used by linked data providers. On the one side, this differs from existing ontology-based solutions, which are based on large, monolithic ontologies that provide very rich semantics, but enforce too restrictive ontological choices, hence are shunned by many data providers. On the other side, this also differs from the purely linked data based solutions, which do offer simplicity and flexibility in data publishing, but too little in terms of semantic interoperability. We demonstrate the feasibility of this idea through the actual development of a large scale data integration project involving seven ocean science data repositories from five institutions in the U.S. In addition, we make two contributions as part of this dissertation work, which also play crucial roles in the aforementioned data integration project. First, we develop a collection of more than a dozen ontology design patterns that capture the key notions in the ocean science occurring in the participating data repositories. These patterns contain axiomatization of the key notions and were developed with an intensive involvement from the domain experts. Modeling of the patterns was done in a systematic workflow to ensure modularity, reusability, and flexibility of the whole pattern collection. Second, we propose the so-called pattern views that allow data providers to publish their data in very simple intermediate schema and show that they can greatly assist data providers to publish their data without requiring a thorough understanding of the axiomatization of the patterns

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance