Work

A Software Reference Architecture for Journalistic Knowledge Platforms

Year: 2023

Type: article

Abstract: Newsrooms and journalists today rely on many different artificial-intelligence, big-data and knowledge-based systems to support efficient and high-quality journalism. However, making the different systems work together remains a challenge, calling for new unified journalistic knowledge platforms. A software reference architecture for journalistic knowledge platforms could help news organisations by capturing tried-and-tested best practices and providing a generic blueprint for how their IT infrastructure should evolve. To the best of our knowledge, no suitable architecture has been proposed in the literature. Therefore, this article proposes a software reference architecture for integrating artificial intelligence and knowledge bases to support journalists and newsrooms. The design of the proposed architecture is grounded on the research literature and on our experiences with developing a series of prototypes in collaboration with industry. Our aim is to make it easier for news organisations to evolve their existing independent systems for news production towards integrated knowledge platforms and to direct further research. Because journalists and newsrooms are early adopters of integrated knowledge platforms, our proposal can hopefully also inform architectures in other domains with similar needs.

Source: Knowledge-Based Systems

DOI: 10.1016/j.knosys.2023.110750

Authors: Marc Gallofré Ocaña, Andreas L. Opdahl

Institution: University of Bergen

Language: English

Topic: Journalism and Media Studies

Subfield: Communication

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,130

Funder: Norges Forskningsråd