Taming Big Data: From management and curation to storage and analysis.
Cuso Winter School, February 1-5, 2016, Champéry, Switzerland
- Participation and Programme
- Registration (Deadline 1st of December 2015)
- Schedule and Reading Lists
Participation & Programme
Student participants are asked to bring a poster of their research work, either existing results or ongoing research that they are currently conducting. Further instructions of how their work will be showcased during the Winter School will be sent by email to everyone closer to the event
A more detailed program of the day-to-day seminars will be given as we approach the dates of the Winter School, as well as a suggested reading list so that the participants are better prepared for the material that will be presented
Professor Renée J. Miller (University of Toronto, Canada),
Professor Renée J. Miller will deliver lectures related to the management of big data. More precisely, her topics will include:
- The management of data when their formats are heterogeneous, e.g. when it comes from data sources with disparate models.
- The algorithms involved when in the transformation and query algorithms that enable the integration of heterogeneous data.
- Algorithms involved find structure and impute missing values in large collections of data in order to improve their Data Quality.
- The topic of Data Curation, which involves the new forms of processing Big Data that have to do with the care of data and ensure it maintains its value over time.
Professor Yannis Velegrakis (University of Trento, Italy)
Professor Yannis Velegrakis is the head of the Data and Information Management group. He will deliver lectures related to big Data Analytics and Information Discovery with a special Emphasis on Social Data. He will also talk about Big Data Quality. In particular, the topics he will cover are:
- Keyword search and other Non-Traditional Query Techniques on Big Data Repositories. Efficient and Effective Techniques.
- Social Data Analytics for End User Understanding (Profiling) and Advanced Recommendation
- Data Quality in Big Data. Understanding Data Quality Problems like Controversies, or Information Incompleteness in large repositories.
Professor Emmanuel Müller (University of Potsdam, Germany)
Professor Emmanuel Müller is head of the Knowledge Discovery and Data Mining Group at Hasso Plattner Institute. He will deliver lectures related to Big Data Analytics, in particular focusing on complex and heterogeneous data resources. His lectures will cover the following topics:
- “Knowledge Discovery”, is more than only automatic analysis of large and complex data. How, to incorporate the humans and their cognitive power into Big Data Analytics?
- “Data Mining on Complex Data”. The complexity of data is a major open challenge for many data mining algorithms. How, to detect patterns in large, high dimensional and heterogeneous data resources?
- “Graph Mining on Attributed Networks”. Beyond traditional network analysis and traditional database systems, big data analytics tries to analyze various different data resources. We focus on modern graph mining technology for attributed networks that is able to analyze both graph structures and attribute information.