Response to Wyssusek’s “On Ontological Foundations of Conceptual Modelling”

Abstract not available

A Roadmap for UEML

International audienceA Roadmap for Unified enterprise modelling languag

Towards Ontological Support for Journalistic Angles

Journalism relies more and more on information and communication technology (ICT). New journalistic ICT platforms continuously harvest potentially news-related information from the internet and try to make it useful for journalists. Because the information sources and formats vary widely, knowledge graphs are emerging as a preferred technology for integrating, enriching, and preparing journalistic information. The paper explores how journalistic knowledge graphs can be augmented with support for news angles, in order to help journalists detect news-worthy events and present them in ways that will interest the intended audience. We argue that finding newsworthy angles on news-related information is important as an example of a more general problem in information science: that of finding the most interesting events and situations in big data sets and presenting those events and situations in the most interesting ways.acceptedVersio

Supporting Newsrooms with Journalistic Knowledge Graph Platforms: Current State and Future Directions

Increasing competition and loss of revenues force newsrooms to explore new digital solutions. The new solutions employ artificial intelligence and big data techniques such as machine learning and knowledge graphs to manage and support the knowledge work needed in all stages of news production. The result is an emerging type of intelligent information system we have called the Journalistic Knowledge Platform (JKP). In this paper, we analyse for the first time knowledge graph-based JKPs in research and practice. We focus on their current state, challenges, opportunities and future directions. Our analysis is based on 14 platforms reported in research carried out in collaboration with news organisations and industry partners and our experiences with developing knowledge graph-based JKPs along with an industry partner. We found that: (a) the most central contribution of JKPs so far is to automate metadata annotation and monitoring tasks; (b) they also increasingly contribute to improving background information and content analysis, speeding-up newsroom workflows and providing newsworthy insights; (c) future JKPs need better mechanisms to extract information from textual and multimedia news items; (d) JKPs can provide a digitalisation path towards reduced production costs and improved information quality while adapting the current workflows of newsrooms to new forms of journalism and readers’ demands.publishedVersio

Challenges and Opportunities for Journalistic Knowledge Platforms

Journalism is under pressure from loss of advertisement and revenues, while experiencing an increase in digital consumption and user demands for quality journalism and trusted sources. Journalistic Knowledge Platforms (JKPs) are an emerging generation of platforms which combine state-of-the-art artificial intelligence (AI) techniques such as knowledge graphs, linked open data (LOD), and natural-language processing (NLP) for transforming newsrooms and leveraging information technologies to increase the quality and lower the cost of news production. In order to drive research and design better JKPs that allow journalists to get most benefits out of them, we need to understand what challenges and opportunities JKPs are facing. This paper presents an overview of the main challenges and opportunities involved in JKPs which have been manually extracted from literature with the support of natural language processing and understanding techniques. These challenges and opportunities are organised in: stakeholders, information, functionalities, components, techniques and other aspects.publishedVersio

A software reference architecture for journalistic knowledge platforms

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.publishedVersio

Addendum to: "Combined Assessment of Software Safety and Security Requirements - An Industrial Evaluation of the CHASSIS Method''

This addendum contains further details about the two case studies reported in our paper Combined Assessment of Software Safety and Security Requirements - An industrial evaluation of the CHASSIS method.publishedVersio

Construction of a relevance knowledge graph with application to the LOCAL news angle

News angles are approaches to journalism content often used to provide a way to present a new report from an event. One particular type of news angle is the LOCAL news angle where a local news outlet focuses on an event by emphasising a local connection. Knowledge graphs are most often used to represent knowledge about a particular entity in the form of relationships to other entities. In this paper we see how we can extract a knowledge sub graph containing entities and relevant relationships that are connected to the locality of a news outlet. The purpose of this graph is to use it for automated journalism or as an aid for the journalist to find local connections to an event, as well as how the local connection relate to the event. We call such a graph a relevance knowledge graph. An algorithm for extracting such a graph from a linked data source like DBpedia is presented and examples of the use of a relevance graph in a LOCAL news angle context are provided.publishedVersio