TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 1

In this class, we will discuss the course organization and provide a basic motivation for and introduction to the course. Readings: Web science: a provocative invitation to computer science, B. Shneiderman, Communications of the ACM 50 25--27 (2007) [Web link] Readings: Chapter 1 & 2, A Framework for Web Science, T. Berners-Lee and W. Hall and J. A. Hendler and K. O'Hara and N. Shadbolt and D. J. Weitzner Foundations and Trends® in Web Science 1 (2006) [Web link] Originally from: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

Object Orientated PHP

To replace Application Scripting and Contemporary Programming Principles

INFO2009 2012-13 Resource Group 15 - Web Science

Web Science - Group 15 created an interactive infographic which informs prospective applicants about the new Web Science undergraduate degrees offered at the University of Southampton, starting in October 2013. Web Science as a new and exciting field of research is also briefly outlined, supported by two video interviews with Dr Les Car, a web scientist.

WAIS seminar: Linked Cultural Media

Wednesday 9th April 2014 Speaker(s): Guus Schreiber Time: 09/04/2014 11:00-11:50 Location: B32/3077 File size: 546Mb Abstract In this talk I will discuss linked data for museums, archives and libraries. This area is known for its knowledge-rich and heterogeneous data landscape. The objects in this field range from old manuscripts to recent TV programs. Challenges in this field include common metadata schema's, inter-linking of the omnipresent vocabularies, cross-collection search strategies, user-generated annotations and object-centric versus event-centric views of data. This work can be seen as part of the rapidly evolving field of digital humanities. Speaker Biography Guus Schreiber Guus is a professor of Intelligent Information Systems at the Department of Computer Science at VU University Amsterdam. Guus’ research interests are mainly in knowledge and ontology engineering with a special interest for applications in the field of cultural heritage. He was one of the key developers of the CommonKADS methodology. Guus acts as chair of W3C groups for Semantic Web standards such as RDF, OWL, SKOS and REFa. His research group is involved in a wide range of national and international research projects. He is now project coordinator of the EU Integrated project No Tube concerned with integration of Web and TV data with the help of semantics and was previously Scientific Director of the EU Network of Excellence “Knowledge Web”.

Bias in the Social Web

Abstract A frequent assumption in Social Media is that its open nature leads to a representative view of the world. In this talk we want to consider bias occurring in the Social Web. We will consider a case study of liquid feedback, a direct democracy platform of the German pirate party as well as models of (non-)discriminating systems. As a conclusion of this talk we stipulate the need of Social Media systems to bias their working according to social norms and to publish the bias they introduce. Speaker Biography: Prof Steffen Staab Steffen studied in Erlangen (Germany), Philadelphia (USA) and Freiburg (Germany) computer science and computational linguistics. Afterwards he worked as researcher at Uni. Stuttgart/Fraunhofer and Univ. Karlsruhe, before he became professor in Koblenz (Germany). Since March 2015 he also holds a chair for Web and Computer Science at Univ. of Southampton sharing his time between here and Koblenz. In his research career he has managed to avoid almost all good advice that he now gives to his team members. Such advise includes focusing on research (vs. company) or concentrating on only one or two research areas (vs. considering ontologies, semantic web, social web, data engineering, text mining, peer-to-peer, multimedia, HCI, services, software modelling and programming and some more). Though, actually, improving how we understand and use text and data is a good common denominator for a lot of Steffen's professional activities.

Data Science, Microsoft and You

In this session we'll explore how Microsoft uses data science and machine learning across it's entire business, from Windows and Office, to Skype and XBox. We'll look at how companies across the world use Microsoft technology for empowering their businesses in many different industries. And we'll look at data science technologies you can use yourselves, such as Azure Machine Learning and Power BI. Finally we'll discuss job opportunities for data scientists and tips on how you can be successful!