Keynote I - Model-driven Support for Reusable Architectural Design Decisions
(Uwe Zdun from Vienna University, Austria)

Every software architecture entails a set of architectural decisions. Software architects capture architectural design decisions for analyzing and understanding, as well as sharing and communicating the rationale and implications of these decisions. A number of recent works have set the focus on gathering, organizing, and effectively leveraging reusable architectural decisions. A prominent way to document such decisions are reusable architectural decision models for providing architectural guidance in software projects. In the talk, we will discuss the modeling of such reusable architectural decision models and automatically establishing consistency of such models with other architecture models, such as component models, using model-driven solutions. Further, we will discuss evidence for this approach in form of an industrial case study and two controlled experiments.

About Uwe Zdun
Uwe Zdun is a full professor for software architecture at the Faculty of Computer Science, University of Vienna. Before that, he worked as an assistant professor at the Vienna University of Technology and the Vienna University of Economics respectively. He received his doctoral degree from the University of Essen in 2002. His research focuses on software architecture, software patterns, modeling of complex software systems, service-oriented systems, domain-specific languages, model-driven development, and empirical software engineering in these areas. Uwe has published more than 130 peer-reviewed articles and is co-author of the professional books "Remoting Patterns – Foundations of Enterprise, Internet, and Realtime Distributed Object Middleware," "Process-Driven SOA – Proven Patterns for Business-IT Alignment," and "Software-Architektur." He has gained significant experiences in leading scientific work and has participated in numerous R&D projects, including ARCS, CONTAINER, INDENICA, COMPAS, S-CUBE, TPMHP, Infinica, SCG, and Sembiz. Uwe is editor of the journal Transactions on Pattern Languages of Programming (TPLoP) published by Springer, and Associate Editor-in-Chief for design and architecture for the IEEE Software magazine.

Keynote II - Towards Open Science: Data Mining and Text Mining Workflows Online
(Nada Lavrač from Jožef Stefan Institute, Ljubljana, Slovenia)

This talk promotes online workflows as means for designing methodologies which can be simply shared and reused in different experimental scenarios. The talk presents a number of innovative workflows, implemented in recently developed web platforms ClowdFlows and TextFlows. In ClowdFlows we illustrate simple data mining workflows implementing the analysis of tabular data, followed by complex relational data mining workflows supporting the analysis of data stored in relational data bases. ClowdFlows provides open access to numerous standard propositional data mining algorithms, to relational data mining systems Aleph, RSD, RelF, RELAGGS and Wordification, as well as the ViperCharts toolbox for results evaluation and visualization. In TextFlows we illustrate standard text processing workflows involving tokenization, stopword removal, POS tagging and stemming/lemmatization, followed by complex text mining and NLP workflows, including cross-context literature-based discovery using the CrossBee text exploration engine.

About Nada Lavrač
Nada Lavrač is Head of Department of Knowledge Technologies at Jožef Stefan Institute, Ljubljana, Slovenia. She is also Professor at the Jožef Stefan International Postgraduate School in Ljubljana and at the University of Nova Gorica. Her main research interests are in Knowledge Technologies, particularly in machine learning, data mining, text mining and knowledge management. Her special interest is relational data mining and supervised descriptive rule induction. She is author of several books, including the recently published Foundations of Rule Learning, Springer 2012. Areas of her applied research include data mining applications in medicine, health care and bioinformatics. Her recent research interests include computational creativity and development of infrastructures for data mining and text mining, which enable experiment repeatability, software sharing and reuse.