Information Systems, Big Data and Knowledge Landscapes

This chapter describes technical approaches that aim to address the challenges involved in finding accurate and up-to-date information. We focus on two challenges: the challenge of finding all relevant information and the challenge of determining the reliability of this information. The chapter examines the potential contributions of current technical solutions for navigating available knowledge. The first challenge, the challenge of finding relevant information, can be addressed by natural language processing (NLP) technologies that process text automatically and extract information from them at a highly detailed level. This includes the topic of the text, what is being claimed about this topic, by whom and based on what evidence. We describe the system architecture of tools providing this information and report on the accuracy of the technologies involved according to the latest state of the art.

The second challenge, the challenge of determining the transparency of the information found, can be addressed by representing the automatically extracted information using the Grounded Representation and Source Perspective (GRaSP) framework (Fokkens et al. Proceedings of the Workshop Knowledge Resources for the Socio-Economic Sciences and Humanities Associated with RANLP 2017, pp. 19–25, 2017). The chapter offers, therefore, some important practical steps that can be taken in navigating the knowledge landscape more assuredly by deploying the NLP approach. We illustrate how the technologies and representation format work and their current performance through the analysis of the online vaccination debate.