KIT – University of the State of Baden-Württemberg andNational Large-scale Research Center of the Helmholtz Association

Institut AIFB – Angewandte Informatik und Formale Beschreibungsverfahren

www.kit.edu

Diversity and the Semantic Web

Elena Simperl and Denny Vrandečić

Institut AIFB2

The loss of serendipity

Institut AIFB3

The myth of numerical methods

Institut AIFB4

Fragmentation, ghettoization, polarization

Institut AIFB5

Policy and decision-making

Institut AIFB6

Challenges

Understand the emergence and impact of biases in (collaborative) content prosumption.

Different parties are likely to have different points of view andshould be able to express and talk about them.

There is no way to ‚agree to disagree‘ on the Semantic Web!

Core activities and underlying techniques are (implicitly) biased.Modeling, choice of ontology to be used, definition of mappings, lifting to RDF, selection of data sets, aggregation, visualization…

Institut AIFB7

Challenges (2)

Identify, represent and predict biases.

Models to represent provenance, trust, quality…for different typesof content, and as part of the activities listed above.

Models to predict the socio-technical mechanisms leading tobiases.

Opinion mining and sentiment analysis.

Institut AIFB8

Challenges (3)

Design diversity-minded data and information managementalgorithms

…taking into account both producer and consumer biases.

Make biases explicit.

Augment ranking, filtering, recommendation, visualization…

KIT – University of the State of Baden-Württemberg andNational Large-scale Research Center of the Helmholtz Association

Institut AIFB – Angewandte Informatik und Formale Beschreibungsverfahren

www.kit.edu