Scalable Tools for Linked Data Analytics (2016)

  • Welcome to Scalable Tools for Linked Data Analytics


    Description: With recent advances of the Semantic Web, more and more data is becoming available as Linked Open Data, i.e., the data is publicly available to everyone free of charge (Open Data) and the data itself contains links to other sources on the Web (Linked Data). The standard data format for such data sources is RDF (Resource Description Framework), which can be queried using SPARQL as query language. It thus becomes increasingly attractive to analyze this data, either alone or in combination
    With other data sources. However, analytical processing of the huge amount of data that is available represents challenges. Particular challenges in this context are analyzing and integrating Linked Data as well as formulating and processing analytical queries as they are known in the context of data warehousing and business intelligence. Both often require cloud-based techniques to ensure scalability. 
    This course briefly introduces the basics of Linked Open Data as well as the standards it is based upon, such as RDF and SPARQL. The course will emphasize the importance and meaning of analyzing and integrating Linked Open Data and discuss appropriate techniques to achieve this goal. Furthermore, the course will cover how to formulate analytical queries and how to process them efficiently at large scale. 

    Organizer:

    Associate Professor Katja Hose, khose@cs.aau.dk

    Lecturers:

    TBD

    ECTS:

    2

    Time:

    12-13 September, 2016

    Place: 

    Zip code: 

    City: 

    Number of seats:

    Deadline: 22 August, 2016

    Important information concerning PhD courses 
    We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.