1st Workshop on Data Science: Methods, Technology and Applications (DSci15)

Co-located with the 11th International Conference on Semantic Systems SEMANTiCS, http://www.semantics.cc
To be held on 15th of September 2015, 09.00 to 17.00 CEST in Vienna, Austria

The term ‘Data Science’ is being popularized by Internet companies in Silicon Valley such as LinkedIn and Twitter to refer to the leads of their data analytics teams. Declared by Harvard Business Review as the ‘sexiest job of the 21st century’, the term is typically linked, in its current definition, to a number of core areas of expertise, from the ability to operate high-performance computing clusters and cloud-based infrastructures, to the know-how that is required to devise and apply sophisticated and scalable analytics techniques, and the creativity involved in designing powerful visualizations. Research in this space tends to be equally diverse, bridging between computing, statistics, and user experience design to devise novel frameworks, algorithms and tools that master the scale and complexity of an increasingly data-driven world.

This workshop is meant as an opportunity to bring together researchers and practitioners interested in data science to present their ideas and discuss the most important scientific, technical and socio-economical challenges of this emerging field. We welcome participants from industry and academia, as well as active members of local meet-up initiatives to join us at the University of Economics and Business on September 15th, 2015 in an international, multidisciplinary forum to share their experiences and explore the newest trends in data science.

Our goal is to put together a workshop that allows researchers in different academic disciplines to present their newest work, including work in progress; learn about the problems, needs, and existing data science solutions in industry and the public sector; and discuss strategies on how to establish data science as a future, truly interdisciplinary field in research, education, and technology development.

The program will feature a mix of invited talks and a smaller selection of submitted contributions, as well as a panel on data science education. Scientists and professionals from all disciplines and sectors are invited to attend and share their knowledge and experiences.

DSci15 - Schedule and Program

Morning: Data Aggregation and Analytics

Afternoon: Analytics, Visualization and Cross-Cutting Issues

 

Bios and Talk Abstracts

Sensing the Earth via six billion human sensors (Fabio Ciravenga)

Abstract: The ubiquitous use of mobile devices and their use for social activities makes possible to sense and see our planet through the eyes and the senses of billion of citizens. This s

ensing can use different approaches, from participatory sensing (where citizen expressly provide the data and information  e.g. as part of a citizen science project or to help manage emergency situations), to opportunistic sensing (where data and information provided for different reasons are tracked and used to understand events and situations), to plain surveillance where citizens are sensed in their activities for security and/or emergency reasons.

In this talk I will discuss my experience in releasing technology to and working in the emergency control rooms of very large events involving hundreds of thousands of participants to help identify planned and unplanned situations through mobile sensing and the large scale analysis of social media. Applications range from tackling natural and man-made disasters (floods, earthquakes, large fires, etc.), to overseeing City and Music Festivals. The task requires high focus on the geographic area, understanding of the social context and the event nature, as well as instinct and experience to cope with large crowds and their sometimes erratic behaviour. It is fundamentally a human centred task that requires important support by computers, as long uncomfortable shifts may be involved (sometimes 24/7) and the amount of material to cope with can be huge (millions of messages and pictures to sift through). In this talk I will discuss the technological and social solutions and challenges, focussing mainly on social media analysis.

 

Bio: Fabio Ciravegna is Professor of Language and Knowledge Technologies at the Department of Computer Science at the University of Sheffield. His research field concerns Knowledge and Information Management over large scale, covering 3 main areas: (i) How to capture information over large scale from multiple sources and devices (the Web, the Social Web, distributed organisational archives, mobile devices, etc.), (ii) how to use the captured information (e.g. for knowledge management, business intelligence, customer analysis, management of large scale events, etc.); and (iii) how to communicate the information (to final users, problem owners, etc.). He is the director of the European Project WeSenseIt on citizen observatories of water and principal investigator in the EPSRC project LODIE (Large Scale Information Extraction using Linked Open Data). He has developed with Neil Ireson and Vita Lanfranchi methodologies for event monitoring in social media that have been used to support the emergency services and organisers in several large scale events involving hundreds of thousands of people; among them the Glastonbury Festival (200,000 participants), the Bristol Harbour Festival (250,000), the Tour de France (UK part), the evacuation of 30,000 people from the City of Vicenza and many others. He has co-created two companies: K-Now Ltd who commercialises the social media analysis technology and The Floow Ltd who develops technology currently monitoring hundreds of thousands of drivers for motor insurance via mobile phones.

 

Machine Learning Techniques for Recommender Systems (Alexandros Karatzoglou)

Abstract: I will provide a quick overview of the most commonly used machine learning methods employed in Recommender Systems. Collaborative Filtering has been the most widely used method for recommendation, due to the big commercial interest in recommender systems several new techniques have been developed for CF. Among the most popular ones are memory-based methods and factor models. Moreover recent developments in deep learning have also had an impact on the field of recommender systems.

Bio: Alexandros is a Senior Research Scientist at Telefonica Research working on Machine Learning. He has over 40 papers in the  field and has won 3 best paper awards at the ACM RecSys and ECMLPKDD conferences. He has developed several ranking techniques for collaborative filtering, context-aware recommendation methods and techniques for recommendations in a social network. He is also the author of the core machine learning R package kernlab, and enjoys giving lectures on Machine Learning, Recommender Systems and R.

 

Mapping Pervasive Surveillance and the Role of Big Data (Erich Möchel)

Abstract: European capitals are under massive surveillance by espionage networks located on diplomatic premises. Main targets are the mobile phone systems of civil society. Overview of identified "Five Eyes"-Stations and identified parts of their wireless backbone in Vienna. How open government data could be used for a project to re-engineer and map the entire "Five Eyes" network in Vienna.

 

Datajournalism: Translating Data into Stories (Michael Bauer)

Abstract Data has become an important source in journalism. Around the world data journalists strive to tell compelling stories using data as an additional source. The availability of easy to use tools and techniques allows more and more journalists to explore databases. While data journalism sounds compelling as an idea it faces hard constraints in newsrooms. What do journalists need to turn data into
narratives?

Bio: Michael Bauer is a data geek working as a journalist with the austrian newspaper Der Standard. Previously he was a biomedical researcher, activist and trainer.

 

Looking under the Hood of Interactive Data Visualizations (Rudolf Titl, Markus Wallisch)

Abstract: In this talk, Rudolf will layout guidelines for designing and building effective data visualizations. Along the way, he will look at use cases of data visualizations that are great examples of data-driven narratives. Building upon these principles, Markus will dive into the technology behind modern visualizations, discussing best practices to use, as well as, current and future challenges.

Bios: Rudolf is an Information Designer with backgrounds in new media, interaction design, and cartography, who works mainly in data-related design, creating work ranging from data visualizations to rich data-driven stories. He is the Co-Founder and CEO of interactiv.es, an information design studio based in Vienna. Markus is a Full Stack Software Developer with backgrounds in computer science. He’s been working in the industry for years now building award-winning digital experiences, from powerful backends to engaging frontends, for a variety of clients. He is the Co-Founder and CTO of interactiv.es, an information design studio based in Vienna. 

 

Organizers

• Bernhard Haslhofer (AIT - Austrian Institute of Technology), 
• Elena Simperl (Univ. Southampton), 
• Rainer Stütz (AIT - Austrian Institute of Technology), 
• Ingo Feinerer (FH Wiener Neustadt)

supported by

Registration for attendance

Scientists and professionals from all disciplines and sectors are invited to attend and share their knowledge and experiences.