ProDataMarket: A data marketplace for monetizing linked data

Linked data has emerged as an interesting technology for Publishing structured data on the Web but also as a powerful mechanism for integrating disparate data sources. Various tools and approaches have been developed in the semantic Web community to produce and consume linked data, however little attention has been paid to monetization of linked data. In this paper we introduce a data marketplace – proDataMarket – that enables data providers to generate, advertise, and sell linked data, and data consumers to purchase linked data on the marketplace. The marketplace was originally designed with a focus on geospatial linked data (targeting property-related data providers and consumers) but its capabilities are generic and can be used for data in various domains. This demo will highlight the capabilities offered to the providers and consumers of the data made available on the marketplace.publishedVersio

Data Quality Barriers for Transparency in Public Procurement

Governments need to be accountable and transparent for their public spending decisions in order to prevent losses through fraud and corruption as well as to build healthy and sustainable economies. Open data act as a major instrument in this respect by enabling public administrations, service providers, data journalists, transparency activists, and regular citizens to identify fraud or uncompetitive markets through connecting related, heterogeneous, and originally unconnected data sources. To this end, in this article, we present our experience in the case of Slovenia, where we successfully applied a number of anomaly detection techniques over a set of open disparate data sets integrated into a Knowledge Graph, including procurement, company, and spending data, through a linked data-based platform called TheyBuyForYou. We then report a set of guidelines for publishing high quality procurement data for better procurement analytics, since our experience has shown us that there are significant shortcomings in the quality of data being published. This article contributes to enhanced policy making by guiding public administrations at local, regional, and national levels on how to improve the way they publish and use procurement-related data; developing technologies and solutions that buyers in the public and private sectors can use and adapt to become more transparent, make markets more competitive, and reduce waste and fraud; and providing a Knowledge Graph, which is a data resource that is designed to facilitate integration across multiple data silos by showing how it adds context and domain knowledge to machine-learning-based procurement analytics.publishedVersio

Ontology extraction for coreference chaining

The KunDoc project investigates coreference chaining with ontology-based methods. In this paper, we discuss knowledge-based methods for coreference chaining and in particular the use of ontologies and their acquisition from a corpus. We present the KunDoc methodology and its implementation. We use concepts and their interrelations extracted from a corpus of Norwegian newspaper articles to build up domain-specific ontologies which contribute with selectional restrictions on possible co-referents. We expect to see an improvement over methods that do not employ any semantic knowledge

Dreistadt: A language enabled MOO for language learning

Dreistadt is an educational MOO (Multi User Domain, Object Oriented) for language learning. It presents a virtual world in which learners of German communicate with their fellow learners, teachers and native language users in other locations via the Internet. While the original Dreistadt had an artificial command language for interaction with the system, we have provided it with natural language processing capabilities, in order to allow a more seamless linguistic interaction. For this purpose, an NLP interface for controlled German has been added. The student's natural language commands are translated to system internal instructions by a set of syntactic, semantic and pragmatic analysis tools. The system is capable of handling pronouns and other referring expressions by applying domain knowledge and includes an inferencing component based on predicate logic

Sharing economy services as human-machine networks: Implications for policy making

The emerging sharing economy has important policy implications. To strengthen the basis for policy making, we present an interview study involving sharing economy service owners, policy maker representatives, and research experts. Here, we analyse sharing economy services as human-machine networks, with particular attention to the networked actors and the relations between these, as well as the extent and structure of the sharing economy networks. The study illuminates key challenges and goals for sharing economy services from the perspective of service owners. Implications for policy making are discussed in terms of government regulation as well as self-imposed policies within and across sharing economy service providers.Sharing economy services as human-machine networks: Implications for policy makingacceptedVersio

Digital samhandling og datadeling i bygge-, anleggs- og eiendomsnæringen

Bygge-, anleggs- og eiendomsnæringen (BAE-næringen) er overmoden for et digitalt skifte. BAE er en av Norges store fastlandsnæringer, men produktivitetsutviklingen har vært lav1 og digitaliseringen går sakte2. BAE-næringen er, på lik linje med andre sektorer, eksponert for en rekke trender og endringsprosesser. Utviklingen drives hovedsakelig av tre trender: dyptgripende endringer som følge av teknologiutvikling, økte krav til bærekraftig forretningsdrift, samt digitalisering av næring og samfunn. Det å effektivt kunne dele og utveksle data og informasjon mellom aktører langs verdikjeden (f.eks. mel¬lom byggherre, entreprenør og underleverandører og bygevarehandel) er i mange sammenhenger påpekt som en utløsende faktor for digitaliseringen av sektorer. Når digitale verktøy tas i bruk, produseres det data som vil være nyttige for automatisering og effektivisering av prosesser i hele økosystemet. Datadeling har blitt påpekt som essensielt for konkurransekraften f.eks. innen olje og gass (Konkraft-rapport 2018) eller helse og omsorg, gjennom deling av data i pasientjournalsystemer. Bransjens eget veikart for digitalisering3 ble lagt frem allerede for fire år siden. I mellomtiden har vi ob¬servert at digitale teknologier tas i bruk og ny teknologi rulles ut, men bransjen er fortsatt langt unna den digitale transformasjonen som er nødvendig for å oppnå veikartets ambisiøse målsettinger. Mangel på digital samhandling, som for eksempel BIM-verktøy som ikke kommuniserer på tvers av disiplinene som er involvert i anleggsprosesser, usikkerhet på hvordan data fra f.eks. sensorer kan brukes, nevnes her i mange sammenhenger. Til tross for et fåtall lovende initiativer som blant annet pilotene som implementeres i regi av BIM-verdinettverk, arbeid i Standard Norge og initiativ fra buildingSMART Norge er det en lang vei å gå. Byggenæringens Landsforening har i 2020 oppdatert sitt digitale veikart ved å konkretisere anbefalinger til forskjellige deler av bransjen4. I denne rapporten ønsker vi derfor å dele våre erfaringer og belyse datadeling og betydningen for BAE-næringen. Etter en kort oversikt av trendene som driver digitaliseringen av næringen tar vi utgang¬spunkt i ulike typer digitaliseringsaktiviteter som beskriver hva datadelingen vil bety for sektoren. Vi vil beskrive de ulike arkitekturmønstrene for datadeling og -utveksling, mulige konsekvenser for aktørene, og konkluderer med anbefalinger for bransjen og forvaltningen

Interacting with subterranean infrastructure linked data using augmented reality

Subterranean infrastructure damages caused by excavation works of all kinds are costly and potentially dangerous for workers. Such damages are often caused by poor subterranean data or inappropriate use of the existing data. We aim to provide solutions and services that will hinder obstacles related to the use of subterranean infrastructure data to ensure less damage and less time spent on finding and integrating data about subterranean infrastructure. The result of the work reported in this paper is an augmented reality application that can provide users the ability to see what subterranean infrastructure is located at a given physical location. In this paper we demonstrate a method to create such an application using Linked Data technologies.publishedVersio