Tania Cerquitelli

Bernhard Thalheim

Mirjana Ivanović

Klaus-Dieter Schewe

Barbara Catania

Ajantha Dahanayake

Mārīte Kirikova

Petr Šaloun

Elena Baralis

Pietro Michiardi

This book constitutes the thoroughly refereed short papers, workshops and Doctoral Consortium papers of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016. The 11 short papers and one historical paper were carefully selected and reviewed from 85 submissions. The rest of papers was selected from reviewing processes of 2 workshops and Doctoral Consortium. The papers are organized in topical sections on ADBIS Short Papers, Third International Workshop on Big Data Applications and Principles (BigDap 2016), Second International Workshop on Data Centered Smart Applications (DCSA 2016) and ADBIS Doctoral Consortium.

ADBIS 2016 Short Papers and Workshops, BigDap, DCSA, DC, Prague, Czech Republic, August 28-31, 2016, Proceedings

New Trends in Databases and Information Systems

Enrico Macii

Nikolaos Nikolakis

Niamh O’Mahony

Massimo Ippolito

Sotirios Makris

This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.

Architectures, Methodologies, and Use-cases

Predictive Maintenance in Smart Factories

András Benczúr

Tomáš Horváth

Silvia Chiusano

Csaba Sidló

Peter Z. Revesz

This book constitutes the thoroughly refereed short papers, workshops and doctoral consortium papers of the 22th European Conference on Advances in Databases and Information Systems, ADBIS 2018, held in Budapest, Hungary, in September 2018. The 20 full and the 4 short workshop papers as well as the 3 doctoral consortium papers were carefully reviewed and selected from 54 submissions to the workshops and 6 submissions to the doctoral consortium. Furthermore, there are 10 short papers included, which were accepted for the main conference. The papers are organized according to the 6 workshops and the doctoral consortium: ADBIS 2018 short papers; First Workshop on Advances on Big Data Management, Analytics, Data Privacy and Security, BigDataMAPS 2018; First International Workshop on New Frontiers on Meta-data Management and Usage, M2U 2018; First Citizen Science Applications and Citizen Databases Workshop, CSADB 2018; First International Workshop on Articial Intelligence for Question Answering, AI*QA 2018; First International Workshop on BIG Data Storage, Processing and Mining for Personalized MEDicine, BIGPMED 2018; First Workshop on Current Trends in Contemporary Information Systems and Their Architectures, ISTREND 2018; Doctoral Consortium.

ADBIS 2018 Short Papers and Workshops, AI*QA, BIGPMED, CSACDB, M2U, BigDataMAPS, ISTREND, DC, Budapest, Hungary, September, 2-5, 2018, Proceedings

Frank Pasquale

Daniele Quercia

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

Transparent Data Mining for Big and Small Data

Tania Cerquitelli

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