1st International Workshop on Data Science: Methodologies and Use-Cases (DaS 2017)

DaS 2017


Architecture Computing Systems Data Mining & Analysis Databases & Information Systems Uncategorized



WORKSHOP OVERVIEW
Data science is an interdisciplinary field about scientific processes, methodologies, and systems to extract useful knowledge or insights from data in various forms. Data can be analyzed using data mining, machine learning, data analysis and statistics, optimizing processes and maximizing the knowledge exploitation in real-life settings.
DaS 2017 is a workshop aimed at fostering and sharing research and innovation on data science. The workshop will allow researchers and practitioners to exchange their ideas and experiences on designing and developing data science applications, to discuss the main open issues and to share novel solutions for data management and analytics.
Researchers are encouraged to submit their papers describing systems, platforms, algorithms, methodologies and applications addressing all facets of a data-driven technological solution. Industrial implementations of data science applications, design and deployment experience reports on various issues raising in data science projects are particularly welcome. We call for research and experience papers as well as demonstration proposals covering any aspect of a data science application (e.g., smart cities, e-commerce, social networks, bio-sciences and healthcare, business analytics and finance, Internet of Things).
TOPICS OF INTEREST (include but are not limited to the following):
- Research challenges on data management and analytics
- Methodologies, models, algorithms, and architectures for data science
- Scalable and/or descriptive data mining and Machine learning techniques for knowledge discovery
- Cloud computing techniques for data science
- Parallel and distributed computing for data science
- Big Data frameworks and architectures
- Data warehouses and large-scale databases
- Personalization and recommendation techniques for Big Data
- Visualization methods for data-intensive applications
- Case studies on data management and analytics for small and big data
- Experiences with data-driven project development and deployment
In one of – though not limited to – the following application scenarios:
- Bio-sciences and healthcare
- Internet of Things
- Urban economy and urban environments
- Financial applications
- Business analytics and finance
- User-generated content (like tweets, micro-blog)
- Industry 4.0
SUBMISSION INSTRUCTIONS
Submissions should present original results and substantial new work not currently under review or published elsewhere. This workshop accepts:
- Research papers (up to 10 pages) including novel approaches for data science methodologies and algorithms.
- Application papers (up to 5 pages) describing data science use-cases.
- Industrial papers (up to 4 pages) describing experiences in the industry sectors.
- Demo proposals (up to 2 pages) describing the demo flow.
Papers must comply with the Springer formatting guidelines (instructions for authors are available at http://www.springer.com/computer/lncs?SGWID=0-164-12-73062-0). Papers should be formattex in LATEX and submitted in PDF format using the online submission system https://easychair.org/conferences/?conf=das2017
PUBLICATION
Workshop papers will be published by Springer-Verlag in the Communications in Computer and Information Science (CCIS) series.
The authors of the best workshop papers will be invited to prepare extended versions of their papers after the workshop. Following an additional round of reviews, the extended papers will appear in a special issue of Information System frontiers, Springer (Impact Factor = 0.761).
WORKSHOP CO-CHAIRS:
- Tania Cerquitelli (Politecnico di Torino, Italy. E-mail: tania DOT cerquitelli AT polito DOT it)
- Silvia Chiusano (Politecnico di Torino, Italy. E-mail: silvia DOT chiusano AT polito DOT it)
- Natalija Kozmina (University of Latvia, Latvia. E-mail: natalija DOT kozmina AT lu DOT lv)
PROGRAM COMMITTEE:
- Julien Aligon (University of Toulouse - IRIT, France)
- Göran Falkman (University of Skövde, Sweden)
- Fabio Fassetti (Università della Calabria, Italy)
- Juozas Gordevicius (Institute of Biotechnology, Lithuania)
- Patrick Marcel (University François Rabelais of Tours, France)
- Erik Perjons (Stockholm university, Sweden)
- Emanuele Rabosio (Politecnico di Milano, Italy)
- ...
CONTACTS
If you have any question or information request on DaS 2017 workshop, please send an email to tania DOT cerquitelli AT polito DOT IT.