Synote: weaving media fragments and linked data

While end users could easily share and tag the multimedia resources online, the searching and reusing of the inside content of multimedia, such as a certain area within an image or a ten minutes segment within a one-hour video, is still difficult. Linked data is a promising way to interlink media fragments with other resources. Many applications in Web 2.0 have generated large amount of external annotations linked to media fragments. In this paper, we use Synote as the target application to discuss how media fragments could be published together with external annotations following linked data principles. Our design solves the dereferencing, describing and interlinking methods problems in interlinking multimedia. We also implement a model to let Google index media fragments which improves media fragments' online presence. The evaluation shows that our design can successfully publish media fragments and annotations for both semantic Web agents and traditional search engines. Publishing media fragments using the design we describe in this paper will lead to better indexing of multimedia resources and their consequent findabilit

Linking Data Across Universities: An Integrated Video Lectures Dataset

This paper presents our work and experience interlinking educational information across universities through the use of Linked Data principles and technologies. More specifically this paper is focused on selecting, extracting, structuring and interlinking information of video lectures produced by 27 different educational institutions. For this purpose, selected information from several websites and YouTube channels have been scraped and structured according to well-known vocabularies, like FOAF 1, or the W3C Ontology for Media Resources 2. To integrate this information, the extracted videos have been categorized under a common classification space, the taxonomy defined by the Open Directory Project 3. An evaluation of this categorization process has been conducted obtaining a 98% degree of coverage and 89% degree of correctness. As a result of this process a new Linked Data dataset has been released containing more than 14,000 video lectures from 27 different institutions and categorized under a common classification scheme

The instantiation of Omnipaper RDF prototype in the context of scientific publications

The purpose of this paper is to present an instance of the system developed in the OmniPaper project, regarding the mechanisms of distributed information retrieval. These mechanisms were developed for newspapers’ articles and they were then instantiated in the context of the scientific publication. Another goal concerns the use of a central metadatabase developed to accomplish the syndication of contents, through the RSS approach. Design/methodology/approach One of the steps of the system’s development was the definition of the metadata layer that supports the research and the navigation functionalities as well as the contents’ syndication. Several tasks were performed for the definition of the metadata layer, namely: (1) analysis of several metadata standard vocabularies; (2) Selection of the metadata elements; (3) Definition of an application profile and the RSS template; (4) Development of a metadatabase, through the use of a native RDF database management system to store the RSS descriptions of the scientific publications; (5) Implementation of the search and navigation processes developed in the prototype through the use of the RDFS version of the WordNet and the RDFS version of classification system of Association for Computing Machinery Computing Classification System (ACM CCS); finally (5) Tests and validation of all developed functionalities. Findings and value The OmniPaper system can be instantiated to other domains other than news published in newspapers. The RSS technology is well suited for handling the description of scientific contents. RDF records that were used in the OmniPaper RDF prototype were replaced by RSS. The subject and lexical thesauri were kept. This strong metadata layer allows the creation of several services that facilitate the conceptual search of scientific contents. Originality and value of paper This paper presents a system that uses a central metadatabase to support conceptual searching mechanisms. The metadatabase consists of RDF triples generated from: (1) RSS files that were, by their turn generated from OAI-PMH harvested metadata records; (2) a controlled vocabulary (ACM-CCS) implemented in RDF Schema and (3) an RDF version of WordNet. This is a solution for a value-added service for the scientific community that is fully based in state-of-the-art standard technologies and is fully open for integration with other systems. Moreover this could be implemented by journals to improve the current mechanisms used to access, distribute and disseminate the scientific research developments. Research limitations/implications (if applicable) The system implemented was tested but not evaluated in a real environment with specific users

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

The Omnipaper metadata RDF/XML prototype implementation

Omnipaper (Smart Access to European Newspapers, IST-2001-32174) is a project from the European Commission IST program (Information Society Technologies) that investigates and proposes ways for access to different types of distributed information sources. This article intends to introduce the technology Resource Description Framework - RDF, developed by W3C for the Web based on metadata, and its practical use in the Omnipaper project, which the authors are involved. We intend to achieve the implementation of a prototype that enables users (professional journalists and occasional users) to have simultaneous and structured access to the articles of a large number of digital European news providers. Omnipaper is not a project about digitalization of news, but about bringing digitized news originating from various sources (and in various formats) together. In this article will be described the procedure implemented in the description of our newspaper articles using the RDF technology, followed by a elaborated description on the manipulation process and treatment of the information structured in RDF, through the RDF Gateway

Towards a Big Data Platform for News Angles

Finding good angles on news events is a central journalistic and editorial skill. As news work becomes increasingly computer-assisted and big-data based, journalistic tools therefore need to become better able to support news angles too. This paper outlines a big-data platform that is able to suggest appropriate angles on news events to journalists. We first clarify and discuss the central characteristics of news angles. We then proceed to outline a big-data architecture that can propose news angles. Important areas for further work include: representing news angles formally; identifying interesting and unexpected angles on unfolding events; and designing a big-data architecture that works on a global scale.publishedVersio

Semantic Knowledge Graphs for the News: A Review

ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different volumes. Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information. It is therefore well-aligned with the needs of news producers and distributors, and it is likely to become increasingly important for the news industry. This article reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news. The purpose is to present an overview of the field; to investigate what it means; and to suggest opportunities and needs for further research and development.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