Dumitru Roman

• Roman, Dumitru; Alexiev, Vladimir; Paniagua, Javier; Elvesæter, Brian; Zernichow, Bjørn Marius von; Soylu, Ahmet; Simeonov, Boyan & Taggart, Chris (2021). The euBusinessGraph Ontology: a Lightweight Ontology for Harmonizing Basic Company Information. Semantic Web Journal.  ISSN 1570-0844. . doi: 10.3233/SW-210424 Vis sammendrag

  Company data, ranging from basic company information such as company name(s) and incorporation date to complex balance sheets and personal data about directors and shareholders, are the foundation that many data value chains depend upon in various sectors (e.g., business information, marketing and sales, etc.). Company data becomes a valuable asset when data is collected and integrated from a variety of sources, both authoritative (e.g., national business registers) and non-authoritative (e.g., company websites). Company data integration is however a difficult task primarily due to the heterogeneity and complexity of company data, and the lack of generally agreed upon semantic descriptions of the concepts in this domain. In this article, we introduce the euBusinessGraph ontology as a lightweight mechanism for harmonising company data for the purpose of aggregating, linking, provisioning and analysing basic company data. The article provides an overview of the related work, ontology scope, ontology development process, explanations of core concepts and relationships, and the implementation of the ontology. Furthermore, we present scenarios where the ontology was used, among others, for publishing company data (business knowledge graph) and for comparing data from various company data providers. The euBusinessGraph ontology serves as an asset not only for enabling various tasks related to company data but also on which various extensions can be built upon.

• Abburu, Sailesh; Berre, Arne J.; Jacoby, Michael; Roman, Dumitru; Stojanovic, Ljiljana & stojanovic, nenad (2020). Cognitive Digital Twins for the Process Industry, In Charlotte Sennersten & Oana Dini (ed.),  COGNITIVE 2020, The Twelfth International Conference on Advanced Cognitive Technologies and Applications.  Think Mind.  ISBN 978-1-61208-780-1.  Cognitive Digital Twins for the Process Industry.
• Abburu, Sailesh; Berre, Arne- Jørgen; Jacoby, Michael; Roman, Dumitru; Stojanovic, Ljiljana & Stojanovic, Nenad (2020). COGNITWIN – Hybrid and Cognitive Digital Twins for the Process Industry, In  2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC).  IEEE.  ISBN 978-1-7281-7037-4.  195.  s 1 - 8 Vis sammendrag

  The concepts of Hybrid and Cognitive Digital Twin are introduced as elements of the next level of process control and automation in the process and manufacturing industry. We propose an architecture for the implementation of Hybrid and Cognitive Twins as part of the COGNITWIN software toolbox. The toolbox is designed to cover cognitive capabilities for optimal operations and maintenance of process equipment and assets, thereby minimizing production overheads and increasing efficiencies for the process industry. Furthermore, we identify a set of relevant use cases in the process industry and discuss the possible applicability and use of the toolbox.

• Dessalk, Yared Dejene; Nikolov, Nikolay; Matskin, Mihhail; Soylu, Ahmet & Roman, Dumitru (2020). Scalable Execution of Big Data Workflows using Software Containers, In Richard Chbeir; Yannis Manolopoulos; Ernesto Damiani & Djamal Benslimane (ed.),  MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems.  ACM Publications.  ISBN 978-1-4503-8115-4.  Chapter.  s 76 - 83 Vis sammendrag

  Big Data processing involves handling large and complex data sets, incorporating different tools and frameworks as well as other processes that help organisations make sense of their data collected from various sources. This set of operations, referred to as Big Data workflows, require taking advantage of the elasticity of cloud infrastructures for scalability. In this paper, we present the design and prototype implementation of a Big Data workflow approach based on the use of software container technologies and message-oriented middleware (MOM) to enable highly scalable workflow execution. The approach is demonstrated in a use case together with a set of experiments that demonstrate the practical applicability of the proposed approach for the scalable execution of Big Data workflows. Furthermore, we present a scalability comparison of our proposed approach with that of Argo Workflows - one of the most prominent tools in the area of Big Data workflows.

• Roman, Dumitru & Soylu, Ahmet (2020). Enabling the European Business Knowledge Graph for Innovative Data-Driven Products and Services. ERCIM News.  ISSN 0926-4981.  (121)
• Samuelsen, Simen; Nikolov, Nikolay; Soylu, Ahmet & Roman, Dumitru (2020). An Approach for Representing and Storing RDF Data in Multi-model Databases, In  14th International Conference on Metadata and Semantics Research (MTSR 2020).  Springer Nature.  ISBN 978-3-030-36598-1.  n/a. Vis sammendrag

  The emergence of NoSQL multi-model databases, nativelysupporting scalable and unified storage and querying of various datamodels, presents new opportunities for storing and managing RDF data.In this paper, we propose an approach to store RDF data in multi-modeldatabases. We identify various aspects of representing the RDF datastructure into a multi-model data structure and discuss their advantagesand disadvantages. Furthermore, we implement and evaluate the pro-posed approach in a prototype using ArangoDB—a popular multi-modeldatabase.

• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Yedro Martínez, Francisco; Kovacic, Matej; Posinkovic, Matej; Makgill, Ian; Taggart, Chris; Simperl, Elena; Lech, Till Christopher & Roman, Dumitru (2020). Enhancing Public Procurement in the European Union Through Constructing and Exploiting an Integrated Knowledge Graph. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  12507, s 430- 446 . doi: 10.1007/978-3-030-62466-8_27 Vis sammendrag

  Public procurement is a large market affecting almost every organisation and individual. Governments need to ensure efficiency, transparency, and accountability, while creating healthy, competitive, and vibrant economies. In this context, we built a platform, consisting of a set of modular APIs and ontologies to publish, curate, integrate, analyse, and visualise an EU-wide, cross-border, and cross-lingual procurement knowledge graph. We developed end-user tools on top of the knowledge graph for anomaly detection and cross-lingual document search. This paper describes our experiences and challenges faced in creating such a platform and knowledge graph and demonstrates the usefulness of Semantic Web technologies for enhancing public procurement.

• Sajid, Salhia; Zernichow, Bjørn Marius von; Soylu, Ahmet & Roman, Dumitru (2019). Predictive Data Transformation Suggestions in Grafterizer Using Machine Learning. Communications in Computer and Information Science.  ISSN 1865-0929.  1057 CCIS, s 137- 149 . doi: 10.1007/978-3-030-36599-8_12 Fulltekst i vitenarkiv. Vis sammendrag

  Data preprocessing is a crucial step in data analysis. A substantial amount of time is spent on data transformation tasks such as data formatting, modification, extraction, and enrichment, typically making it more convenient for users to work with systems that can recommend most relevant transformations for a given dataset. In this paper, we propose an approach for generating relevant data transformation suggestions for tabular data preprocessing using machine learning (specifically, the Random Forest algorithm). The approach is implemented for Grafterizer, a Web-based framework for tabular data cleaning and transformation, and evaluated through a usability study.

• Vega-Gorgojo, Guillermo; Slaughter, Laura; Zernichow, Bjørn Marius von; Nikolov, Nikolay & Roman, Dumitru (2019). Linked Data Exploration With RDF Surveyor. IEEE Access.  ISSN 2169-3536.  7, s 172199- 172213 . doi: 10.1109/ACCESS.2019.2956345 Fulltekst i vitenarkiv. Vis sammendrag

  Linked Data exploration is an essential task in the process of understanding, assessing, and using datasets made available in the Resource Description Framework (RDF) format. Current solutions for exploration of RDF data are mainly targeted at Semantic Web experts, require non-trivial deployments, and do not scale to the increasing amounts of data published in RDF. The lack of simple, intuitive, and efficient solutions for exploring RDF data, especially for lay users, is the main motivation behind the work presented in this paper. We propose RDF Surveyor, an easy-to-use and lightweight tool for exploring RDF datasets. Its visual interface hides the intricacies of Semantic Web technologies from the user, while providing intuitive overviews of datasets, class navigation, and visualization of class instances. Furthermore, RDF Surveyor does not require any installation and can handle large datasets such as DBpedia. We provide a detailed overview of RDF Surveyor and illustrate its capabilities in two different scenarios. We also analyze the uptake, performance and usability of RDF Surveyor, showing its suitability for exploring Linked Data at scale.

• Cutrona, Vincenzo; de Paoli, Flavio; Košmerlj, Aljaž; Nikolov, Nikolay; Palmonari, Matteo; Perales, Fernando & Roman, Dumitru (2019). Semantically-Enabled Optimization of Digital Marketing Campaigns, In Chiara Ghidini; Olaf Hartig; Maria Maleshkova; Vojtěch Svátek; Isabel Cruz; Aidan Hogan; Jie Song; Maxime Lefrançois & Fabien Gandon (ed.),  The Semantic Web – ISWC 2019.  Springer.  ISBN 978-3-030-30795-0.  11779. Vis sammendrag

  Digital marketing is a domain where data analytics are a key factor to gaining competitive advantage and return of investment for companies running and monetizing digital marketing campaigns on, e.g., search engines and social media. In this paper, we propose an end-to-end approach to enrich marketing campaigns performance data with third-party event data (e.g., weather events data) and to analyze the enriched data in order to predict the effect of such events on campaigns’ performance, with the final goal of enabling advanced optimization of the impact of digital marketing campaigns. The use of semantic technologies is central to the proposed approach: event data are made available in a format more amenable to enrichment and analytics, and the actual data enrichment technique is based on semantic data reconciliation. The enriched data are represented as Linked Data and managed in a NoSQL database to enable processing of large amounts of data. We report on the development of a pilot to build a weather-aware digital marketing campaign scheduler for JOT Internet Media—a world leading company in the digital marketing domain that has amassed a huge amount of data on campaigns performance over the years—which predicts the best date and region to launch a marketing campaign within a seven-day timespan. Additionally, we discuss benefits and limitations of applying semantic technologies to deliver better optimization strategies and competitive advantage.

• Maurino, Andrea; Rula, Anisa; Zernichow, Bjørn Marius von; Soto Gomez, Mauricio; Elvesæter, Brian & Roman, Dumitru (2019). Modelling and Linking Company Data in the euBusinessGraph Platform. Proceedings of the ACM SIGMOD International Conference on Management of Data.  ISSN 0730-8078.  s 1- 6 . doi: https://doi.org/10.1145/3336499.3338012 Vis sammendrag

  In the business environment, knowledge of company data is essential for a variety of tasks. The European funded project euBusinessGraph enables the establishment of a company data platform where data providers and consumers can publish and access company data. The core of the platform is the semantic data model that is the conceptual representation of company data in a common way so that it is easier to share and interlink company data. In this paper we show how the unified model and Grafterizer, a tool for manipulating and transforming raw data into Linked Data, support the linking challenge proposed in FEIII 2019. Results show that geographical enrichment of RDF data supports the interlinking process between company entities in different datasets.

• Roman, Dumitru; Tarasova, Tatiana & Paniagua, Javier (2019). MethOSM: A Methodology for Computing Composite Indicators Derived from OpenStreetMap Data. Journal of Spatial Information Science.  ISSN 1948-660X.  (19), s 3- 27 . doi: 10.5311/JOSIS.2019.19.491 Vis sammendrag

  The task of computing composite indicators to define and analyze complex social, economic, political, or environmental phenomena has traditionally been the exclusive competence of statistical offices. Nowadays, the availability of increasing volumes of data and the emergence of the open data movement have enabled individuals and businesses affordable access to all kinds of datasets that can be used as valuable input to compute indicators. OpenStreetMap (OSM) is a good example of this. It has been used as a baseline to compute indicators in areas where official data is scarce or difficult to access. Although the extraction and application of OSM data to compute indicators is an attractive proposition, this practice is by no means hassle-free. The use of OSM reveals a number of challenges that are usually addressed with ad-hoc and often overlapping solutions. In this context, this paper proposes MethOSM—a systematic methodology for computing indicators derived from OSM data. By applying MethOSM, the computation task is divided into four steps, with each step having a clear goal and a set of guidelines to apply. In this way, the methodology contributes to an effective and efficient use of OSM data for the purpose of computing indicators. To demonstrate its use, we apply MethOSM to a number of indicators used for real estate valuation of properties in Italy.

• Simperl, Elena; Corcho, Oscar; Grobelnik, Marko; Roman, Dumitru; Soylu, Ahmet; Ruíz, María Jesús Fernández; Gatti, Stefano; Taggart, Chris; Klima, Urška Skok; Uliana, Annie Ferrari; Makgill, Ian & Lech, Till Christopher (2019). Towards a Knowledge Graph Based Platform for Public Procurement. Communications in Computer and Information Science.  ISSN 1865-0929.  846, s 317- 323 . doi: 10.1007/978-3-030-14401-2_29 Fulltekst i vitenarkiv.
• Soylu, Ahmet; Elvesæter, Brian; Turk, Philip; Roman, Dumitru; Corcho, Oscar; Simperl, Elena; Konstantinidis, George & Lech, Till Christopher (2019). Towards an Ontology for Public Procurement Based on the Open Contracting Data Standard. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  11701 LNCS, s 230- 237 . doi: 10.1007/978-3-030-29374-1_19 Vis sammendrag

  The release of a growing amount of open procurement data led to various initiatives for harmonising the data being provided. Among others, the Open Contracting Data Standard (OCDS) is highly relevant due to its high practical value and increasing traction. OCDS defines a common data model for publishing structured data throughout most of the stages of a contracting process. OCDS is document-oriented and focuses on packaging and delivering relevant data in an iterative and event-driven manner through a series of releases. Ontologies, beyond providing uniform access to heterogeneous procurement data, could enable integration with related data sets such as with supplier data for advanced analytics and insight extraction. Therefore, we developed an ontology, the “OCDS ontology”, by using OCDS’ main domain perspective and vocabulary, since it is an essential source of domain knowledge. In this paper, we provide an overview of the developed ontology.

• Soylu, Ahmet; Elvesæter, Brian; Turk, Philip; Roman, Dumitru; Corcho, Oscar; Simperl, Elena; Makgill, Ian; Taggart, Chris; Grobelnik, Marko & Lech, Till Christopher (2019). An Overview of the TBFY Knowledge Graph for Public Procurement. CEUR Workshop Proceedings.  ISSN 1613-0073.  2456 Vis sammendrag

  A growing amount of public procurement data is being made available in the EU for the purpose of improving the effectiveness, efficiency, transparency, and accountability of government spending. However, there is a large heterogeneity, due to the lack of common data formats and models. To this end, we developed an ontology network for representing and linking tender and company data and ingested relevant data from two prominent data providers into a knowledge graph, called TBFY. In this poster paper, we present an overview of our knowledge graph.

• Flouris, Giorgos; Patkos, Theodore; Chrysakis, Ioannis; Konstantinou, Ioulia; Nikolov, Nikolay; Papadakos, Panagiotis; Pitt, Jeremy; Roman, Dumitru; Stan, Alexandru & Zeginis, Chrysostomos (2018). Towards a collective awareness platform for privacy concerns and expectations. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  11229, s 135- 152 . doi: 10.1007/978-3-030-02610-3_8 Fulltekst i vitenarkiv. Vis sammendrag

  In an increasingly instrumented and inter-connected digital world, citizens generate vast amounts of data, much of it being valuable and a significant part of it being personal. However, controlling who can collect it, limiting what they can do with it, and determining how best to protect it, remain deeply undecided issues. This paper proposes CAPrice, a socio-technical solution based on collective awareness and informed consent, whereby data collection and use by digital products are driven by the expectations and needs of the consumers themselves, through a collaborative participatory process and the configuration of collective privacy norms. The proposed solution relies on a new innovation model that complements existing top-down approaches to data protection, which mainly rely on technical or legal provisions. Ultimately, the CAPrice ecosystem will strengthen the trust bond between service developers and users, encouraging innovation and empowering the individuals to promote their privacy expectations as a quantifiable, community-generated request.

• Roman, Dumitru & Kifer, Michael (2018). ServLog: A unifying logical framework for service modeling and contracting. Semantic Web Journal.  ISSN 1570-0844.  9(2), s 257- 290 . doi: 10.3233/SW-170262 Vis sammendrag

  Implementing semantics-aware services, which includes semantic Web services, requires novel techniques for modeling and analysis. The problems include automated support for service discovery, selection, negotiation, and composition. In addition, support for automated service contracting and contract execution is crucial for any large scale service environment where multiple clients and service providers interact. Many problems in this area involve reasoning, and a number of logic-based methods to handle these problems have emerged in the field of Semantic Web Services. In this paper, we lay down theoretical foundations for service modeling, contracting, and reasoning, which we call ServLog, by developing novel techniques for modeling and reasoning about service contracts with the help of Concurrent Transaction Logic. With this framework, we significantly extend the modeling power of the previous work by allowing expressive data constraints and iterative processes in the specification of services. This approach not only captures typical procedural constructs found in established business process languages, but also greatly extends their functionality, enables declarative specification and reasoning about services, and opens a way for automatic generation of executable business processes from service contracts.

• Roman, Dumitru & Vu, Kien (2018). Enabling Data Markets Using Smart Contracts and Multi-party Computation, In Witold Abramowicz & Adrian Paschke (ed.),  Business Information Systems Workshops. BIS 2018..  Springer.  ISBN 978-3-030-04848-8.  artikkel.  s 258 - 263 Fulltekst i vitenarkiv. Vis sammendrag

  With the emergence of data markets, data have become an asset that is used as part of transactions. Current data markets rely on trusted third parties to manage the data, creating single points of failure with possibly disastrous consequences on data privacy and security. The lack of technical solutions to enforce strong privacy and security guarantees leaves the data markets’ stakeholders (e.g., buyers and sellers of data) vulnerable when they transact data. Smart Contracts and Multi-Party Computation represent examples of emerging technologies that have the potential to guarantee the desired levels of data privacy and security. In this paper, we propose an architecture for data markets based on Smart Contracts and Multi-Party Computation and present a proof of concept prototype developed to demonstrate the feasibility of the proposed architecture.

• Shi, Ling & Roman, Dumitru (2018). Ontologies for the Real Property Domain, In Rajendra Akerkar (ed.),  WIMS '18 Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics, Novi Sad, Serbia — June 25 - 27, 2018.  Association for Computing Machinery (ACM).  ISBN 978-1-4503-5489-9.  artikkel 14. Vis sammendrag

  Real property, also known as real estate, realty or immovable property, is one of the most important assets for the world economy. Real property data is valuable input for decision makers in various domains. Real property data has temporal and spatial characteristics and is distributed across multiple systems. Integration of real property data from legal and business systems (possibly from different countries) with contextual data in related domains is a challenging task that requires cross-domain knowledge. Real property ontologies, capturing relevant domain knowledge in a structured way, are essential in the process of integrating real property data. This paper identifies key aspects of the real property domain from a data integration perspective, and surveys ontologies for real property and its related domains. It analyzes geospatial standards for representing geospatial concepts and attributes relevant to real properties, the Land Administration Domain Model and its implementations, and ontologies for real property transactions and for real property data integration. This survey aims to collect and compare existing real property ontologies and conceptual models, serving as a reference point for ontologies and conceptual models in the real property domain

• Simperl, Elena; Corcho, Oscar; Grobelnik, Marko; Roman, Dumitru; Soylu, Ahmet; Jesús Fernández Ruíz, María; Gatti, Stefano; Taggart, Chris; Skok Klima, Urška; Ferrari Uliana, Annie; Makgill, Ian & Lech, Till Christopher (2018). TheyBuyForYou: Enabling Procurement Data Value Chains. Communications in Computer and Information Science.  ISSN 1865-0929.  1115, s 179- 186 . doi: 10.1007/978-3-030-63161-1_15
• Soylu, Ahmet; Corcho, Oscar; Simperl, Elena; Roman, Dumitru; Martínez, Francisco Yedro; Taggart, Chris; Makgill, Ian; Elvesæter, Brian; Symonds, Ben; McNally, Helen; Konstantinidis, George; Zhao, Yuchen & Lech, Till Christopher (2018). Towards integrating public procurement data into a semantic knowledge graph. CEUR Workshop Proceedings.  ISSN 1613-0073.  2262, s 1- 4 Fulltekst i vitenarkiv. Vis sammendrag

  Public procurement accounts for a substantial part of the public investment and global economy. Therefore, improving effectiveness, efficiency, transparency and accountability of government procurement is of broad interest. To this end, in this poster paper, we present our approach for integrating procurement data, including public spending and corporate data, from multiple sources across the EU into a semantic knowledge graph. We are aiming to improve procurement processes through supporting multiple stake holders, such as government agencies, companies, control authorities, journalists, researchers, and individual citizens.

• Estrada, Jesus; Sánchez, Héctor; Hernanz, Lorena; Checa, María José & Roman, Dumitru (2017). Enabling the Use of Sentinel-2 and LiDAR Data for Common Agriculture Policy Funds Assignment. ISPRS International Journal of Geo-Information.  ISSN 2220-9964.  6(8) . doi: 10.3390/ijgi6080255 Fulltekst i vitenarkiv. Vis sammendrag

  A comprehensive strategy combining remote sensing and field data can be helpful for more effective agriculture management. Satellite data are suitable for monitoring large areas over time, while LiDAR provides specific and accurate data on height and relief. Both types of data can be used for calibration and validation purposes, avoiding field visits and saving useful resources. In this paper, we propose a process for objective and automated identification of agricultural parcel features based on processing and combining Sentinel-2 data (to sense different types of irrigation patterns) and LiDAR data (to detect landscape elements). The proposed process was validated in several use cases in Spain, yielding high accuracy rates in the identification of irrigated areas and landscape elements. An important application example of the work reported in this paper is the European Union (EU) Common Agriculture Policy (CAP) funds assignment service, which would significantly benefit from a more objective and automated process for the identification of irrigated areas and landscape elements, thereby enabling the possibility for the EU to save significant amounts of money yearly.

• Gan, Dennis Yong Chun & Roman, Dumitru (2017). MOBILE BIG DATA: THE SILVER BULLET FOR TELCOS? A CASE STUDY IN THE NORWEGIAN TELCOS MARKET, In Yingcai Xiao & Ajith P. Abraham (ed.),  INTERNATIONAL CONFERENCES COMPUTER GRAPHICS, VISUALIZATION, COMPUTER VISION AND IMAGE PROCESSING 2017 and BIG DATA ANALYTICS, DATA MINING AND COMPUTATIONAL INTELLIGENCE 2017, Lisbon, Portugal July 21 - 23, 2017.  IADIS Press.  ISBN 978-989-8533-66-1.  artikkel.  s 263 - 272 Fulltekst i vitenarkiv. Vis sammendrag

  The telecommunication industry has been undergoing tremendous changes in recent times. It is obvious that the industry is currently going through an identity crisis. Porter’s Five Forces analysis is used in this paper to investigate the current state of the telecommunication industry in Norway today. The dwindling voice revenue of telcos necessitates the race to find the next revenue stream. This study explores the potential of mobile big data as a resource for telcos to gain competitive advantage with the VRIO Framework (Value-Rare-Imitability-Organization) from the Resources-based View(RBV) theory. Multiple case studies with embedded units that are explanatory and exploratory are applied to Norwegian telcos, following an inductive approach. This study finds that the outlook of the telecommunication industry is rather bleak and despite its promises, mobile big data can only provide temporary competitive advantage to the telcos. Mobile big data is valuable, rare and the telcos are organizing their other resources around it to exploit it, however mobile big data is imitable and not unique. The same data can be obtained by their peers in the industry. Instead, the interview data collected from qualitative research in this study has pointed to organizational culture as the resource that can provide sustained competitive advantage to the telcos. In a highly-competitive industry such as the telecommunication industry, telcos have to constantly rely on resources that can give them temporary competitive advantage; the ability to do this will ultimately be a resource itself that will give them sustained competitive advantage. Telcos have to constantly mix, match and reconfigure their different resources and capabilities to address a rapidly changing environment.

• Mahasivam, Nivethika; Nikolov, Nikolay; Sukhobok, Dina & Roman, Dumitru (2017). Data preparation as a service based on Apache Spark. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  10465, s 125- 139 . doi: 10.1007/978-3-319-67262-5_10 Fulltekst i vitenarkiv. Vis sammendrag

  Data preparation is the process of collecting, cleaning and consolidating raw datasets into cleaned data of certain quality. It is an important aspect in almost every data analysis process, and yet it remains tedious and time-consuming. The complexity of the process is further increased by the recent tendency to derive knowledge from very large datasets. Existing data preparation tools provide limited capabilities to effectively process such large volumes of data. On the other hand, frameworks and software libraries that do address the requirements of big data, require expert knowledge in various technical areas. In this paper, we propose a dynamic, service-based, scalable data preparation approach that aims to solve the challenges in data preparation on a large scale, while retaining the accessibility and flexibility provided by data preparation tools. Furthermore, we describe its implementation and integration with an existing framework for data preparation – Grafterizer. Our solution is based on Apache Spark, and exposes application programming interfaces (APIs) to integrate with external tools. Finally, we present experimental results that demonstrate the improvements to the scalability of Grafterizer.

• Nikolov, Nikolay; Sukhobok, Dina; Dragnev, Stefan; Dalgard, Steffen Harald; Elvesæter, Brian; Zernichow, Bjørn Marius von & Roman, Dumitru (2017). DataGraft beta v2: New features and capabilities. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  In this demonstrator, we will introduce the latest features and capabil-ities added to DataGraft – a Data-as-a-Service platform for data preparation and knowledge graph generation. DataGraft provides data transformation, publishing and hosting capabilities that aim to simplify the data publishing lifecycle for data workers (i.e., Open Data publishers, Linked Data developers, data scientists). This demonstrator highlights the recent features added to DataGraft by exempli-fying data publication of statistical data – going from the raw data published at a public portal to published and accessible Linked Data with the help of the tools and features of the platform.

• Roman, Dumitru; Kobernus, Michael John; Ødegård, Rune Åvar; Nikolov, Nikolay; Sukhobok, Dina; Zernichow, Bjørn Marius von & Lech, Till Christopher (2017). ALaDIn: Shining a Light on Air Quality through Data Integration and Machine Learning, In Benoît Otjacques; Patrik Hitzelberger; Stefan Naumann & Wohlgemuth Volker (ed.),  From Science to Society: The Bridge provided by Environmental Informatics, Adjunct Proceedings of the 31st EnviroInfo Conference, Luxembourg, September 13-15. 2017.  Shaker Verlag.  ISBN 978-3-8440-5495-8.  artikkel.  s 293 - 298 Vis sammendrag

  To achieve the necessary level of accuracy when measuring air pollution for scientific purposes, expensive and complicated instrumentation is required. Consequently, only federal, local governments and some industries, collect data of sufficient quality for research, and only for a small number of Air Quality components. This limitation makes it difficult to implement added value services, such as exposure and health assessments. Furthermore, due to increasing urban and peri-urban population density and consequent rise in air pollution, Air Quality management problems are becoming more complex. As a result, there is a vital need for enhanced Air Quality and exposure monitoring capabilities. This has been severely hampered by the high cost of traditional monitoring stations and the lack of high resolution data.

• Roman, Dumitru; Nikolov, Nikolay; Pultier, Antoine; Sukhobok, Dina; Elvesæter, Brian; Berre, Arne- Jørgen; Ye, Xianglin; Dimitrov, Marin; Simov, Alex; Zarev, Momchill; Moynihan, Rick; Roberts, Bill; Berlocher, Ivan; Kim, Seon-Ho; Lee, Tony; Smith, Amanda & Heath, Tom (2017). DataGraft: One-stop-shop for open data management. Semantic Web Journal.  ISSN 1570-0844.  9(4), s 393- 411 . doi: 10.3233/SW-170263 Fulltekst i vitenarkiv. Vis sammendrag

  This paper introduces DataGraft (https://datagraft.net/) – a cloud-based platform for data transformation and publishing. DataGraft was developed to provide better and easier to use tools for data workers and developers (e.g. open data publishers, linked data developers, data scientists) who consider existing approaches to data transformation, hosting, and access too costly and technically complex. DataGraft offers an integrated, flexible, and reliable cloud-based solution for hosted open data management. Key features include flexible management of data transformations (e.g. interactive creation, execution, sharing, reuse) and reliable data hosting services. This paper provides an overview of DataGraft focusing on the rationale, key features and components, and evaluation.

• Roman, Dumitru; Paniagua, Javier; Tarasova, Tatiana; Georgiev, Georgi; Sukhobok, Dina; Nikolov, Nikolay & Lech, Till Christopher (2017). ProDataMarket: A data marketplace for monetizing linked data. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  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.

• Roman, Dumitru; Sukhobok, Dina; Nikolov, Nikolay; Elvesæter, Brian & Pultier, Antoine (2017). The InfraRisk ontology: enabling semantic interoperability for critical infrastructures at risk from natural hazards. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  10574, s 463- 479 . doi: 10.1007/978-3-319-69459-7_31 Fulltekst i vitenarkiv. Vis sammendrag

  Earthquakes, landslides, and other natural hazard events have severe negative socio-economic impacts. Among other consequences, those events can cause damage to infrastructure networks such as roads and railways. Novel methodologies and tools are needed to analyse the potential impacts of extreme natural hazard events and aid in the decision-making process regarding the protection of existing critical road and rail infrastructure as well as the development of new infrastructure. Enabling uniform, integrated, and reliable access to data on historical failures of critical transport infrastructure can help infrastructure managers and scientist from various related areas to better understand, prevent, and mitigate the impact of natural hazards on critical infrastructures. This paper describes the construction of the InfraRisk ontology for representing relevant information about natural hazard events and their impact on infrastructure components. Furthermore, we present a software prototype that visualizes data published using the proposed ontology.

• Shi, Ling; Nikolov, Nikolay; Tarasova, Tatiana & Roman, Dumitru (2017). The ProDataMarket Ontology for Publishing and Integrating Cross-domain Real Property Data. Territorio Italia - Land Administration, Cadastre, Real Estate.  ISSN 2240-7707.  (2), s 11- 35 . doi: 10.14609/Ti_2_17_1e
• Shi, Ling; Pettersen, Bjørg Elsa; Sukhobok, Dina; Nikolov, Nikolay & Roman, Dumitru (2017). Linked data for the Norwegian state of estate reporting service. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  The Norwegian State of Estate (SoE) report includes information about all Norwegian state-owned properties and buildings in the public sector and aims to assist government decision makers to allocate resources more effectively. A Linked Data based approach is presented here to increase the transparency in the government administration, improve the report generating process and also the report quality. Cross- domain government data originated from the business entity register, the cadastral system, the building accessibility register and the old SoE report are acquired, prepared, cleaned, transformed to Linked Data format and published. The source datasets are then integrated, augmented and interlinked before the results are published as a SPARQL endpoint, used for data visualization and report generation.

• Shi, Ling & Roman, Dumitru (2017). From standards and regulations to executable rules: A case study in the Building Accessibility domain. CEUR Workshop Proceedings.  ISSN 1613-0073.  1875 Fulltekst i vitenarkiv. Vis sammendrag

  Regulatory compliance check in the building industry is a complex task that involves cross-domain national and international standards and regulations. This paper introduces a refined approach to extract SWRL rules from building accessibility regulatory texts and then to transform them into executable rules for semi-automatic compliance checking of Building Information Models. The domain ontology model is a key input to the approach and is enriched by new knowledge extracted from the regulatory text. This semantic technology enhanced rule extraction approach standardized the rule extraction process by covering the whole lifecycle from regulatory text to executable rules. It is based on the open standards and applies open source tools and thereby portable and extendable. It conforms to the open BIM principle to support knowledge sharing cross domains and disciplines. The approach is also adaptable to other types of regulatory rules in the building industry.

• Shi, Ling & Roman, Dumitru (2017). Using rules for assessing and improving data quality: A case study for the Norwegian State of Estate report. CEUR Workshop Proceedings.  ISSN 1613-0073.  1875 Fulltekst i vitenarkiv. Vis sammendrag

  Regulatory compliance check in the building industry is a complex task that involves cross-domain national and international standards and regulations. This paper introduces a refined approach to extract SWRL rules from building accessibility regulatory texts and then to transform them into executable rules for semi-automatic compliance checking of Building Information Models. The domain ontology model is a key input to the approach and is enriched by new knowledge extracted from the regulatory text. This semantic technology enhanced rule extraction approach standardized the rule extraction process by covering the whole lifecycle from regulatory text to executable rules. It is based on the open standards and applies open source tools and thereby portable and extendable. It conforms to the open BIM principle to support knowledge sharing cross domains and disciplines. The approach is also adaptable to other types of regulatory rules in the building industry.

• Shi, Ling; Sukhobok, Dina; Nikolov, Nikolay & Roman, Dumitru (2017). Norwegian State of estate report as linked open data. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  10574, s 445- 462 . doi: 10.1007/978-3-319-69459-7_30 Fulltekst i vitenarkiv. Vis sammendrag

  This paper presents the Norwegian State of Estate (SoE) dataset containing data about real estates owned by the central government in Norway. The dataset is produced by integrating cross-domain government datasets including data from sources such as the Norwegian business entity register, cadastral system, building accessibility register and the previous SoE report. The dataset is made available as Linked Data. The Linked Data generation process includes data acquisition, cleaning, transformation, annotation, publishing, augmentation and interlinking the annotated data as well as quality assessment of the interlinked datasets. The dataset is published under the Norwegian License for Open Government Data (NLOD) and serves as a reference point for applications using data on central government real estates, such as generation of the SoE report, searching properties suitable for asylum reception centres, risk assessment for state-owned buildings or a public building application for visitors.

• Sukhobok, Dina; Djordjevic, Divna; Sanvito, Diego; Paniagua, Javier & Roman, Dumitru (2017). Publishing socio-economic territory indices as linked data and their visualization for real estate valuation. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  The correct estimation of the real estate value facilitates decision making in various sectors, such as Public administration or the real estate market. In this paper we demonstrate a method to manage territory scores and property valuation estimations as Linked Data With the help of the proDataMarket technical framework. The demo illustrates how the proDataMarket technical framework can be used to generate, maintain and serve territory and property valuation estimation data With the help of semantic technologies.

• Sukhobok, Dina; Nikolov, Nikolay; Lech, Till Christopher; Moberg, Arnt-Henning; Frantsvåg, Roar; Bergaas, Helene Risti & Roman, Dumitru (2017). Interacting with subterranean infrastructure linked data using augmented reality. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  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.

• Sukhobok, Dina; Nikolov, Nikolay & Roman, Dumitru (2017). Tabular Data Anomaly Patterns, In Muhammad Younas; Irfan Awan & Irena Holubova (ed.),  2017 International Conference on Big Data Innovations and Applications (Innovate-Data), Prague, Czech Republic, Czech Republic, 21-23 Aug. 2017.  IEEE.  ISBN 978-1-5386-0960-6.  artikkel.  s 25 - 34 Fulltekst i vitenarkiv. Vis sammendrag

  One essential and challenging task in data science is data cleaning - the process of identifying and eliminating data anomalies. Different data types, data domains, data acquisition methods, and final purposes of data cleaning have resulted in different approaches in defining data anomalies in the literature. This paper proposes and describes a set of basic data anomalies in the form of anomaly patterns commonly encountered in tabular data, independently of the data domain, data acquisition technique, or the purpose of data cleaning. This set of anomalies can serve as a valuable basis for developing and enhancing software products that provide general-purpose data cleaning facilities and can provide a basis for comparing different tools aimed to support tabular data cleaning capabilities. Furthermore, this paper introduces a set of corresponding data operations suitable for addressing the identified anomaly patterns and introduces Grafterizer - a software framework that implements those data operations

• Sukhobok, Dina; Sanchez, Hector; Estrada, Jesus & Roman, Dumitru (2017). Linked data for common agriculture policy: Enabling semantic querying over sentinel-2 and LiDAR data. CEUR Workshop Proceedings.  ISSN 1613-0073.  1963 Fulltekst i vitenarkiv. Vis sammendrag

  The amount of open and free satellite earth observation data combined with available data from other sectors (e.g. biodiversity, landscape elements, cadaster data) has the potential to enhance decisionmaking processes in various domains. An example of such a domain is agriculture, where the ability to objectively and automatically identify dfferent types of agricultural features (e.g., irrigation patterns and landscape elements) can lead to more effective agriculture management. In this paper we show the possibility to publish and integrate multi-sectoral data from several sources into an existing data-intensive service targeting better and fairer Common Agriculture Policy (CAP) funds assignments to farmers and land owners. We show an end-to-end approach for integrating multi-sectoral data and publishing the result as Linked Data with the help of the DataGraft platform. To demonstrate the use of the resulted dataset, we developed a visualization system prototype showing various information about agricultural parcel features.

• Zernichow, Bjørn Marius von & Roman, Dumitru (2017). A Visual Data Profiling Tool for Data Preparation, In Sandjai Bhulai & Dimitris Kardaras (ed.),  DATA ANALYTICS 2017 : International Conference on Data Analytics, Barcelona, Spain, November 12-16, 2017.  International Academy, Research and Industry Association (IARIA).  ISBN 978-1-61208-603-3.  artikkel.  s 12 - 14 Fulltekst i vitenarkiv. Vis sammendrag

  In this paper, we propose a tool that implements visual data profiling capabilities for data preparation – an essential step in the process of linked data generation. Our tool features visual data profiling – a technique that identifies and visualizes potential data quality issues, relevant data cleaning functions, and an interactive spreadsheet table view. The proposed demonstration of the tool will focus on the use of visual data profiling in a scenario of cleaning and transforming tabular weather data – as a pre-processing step for linked data generation.

• Zernichow, Bjørn Marius von & Roman, Dumitru (2017). Usability of visual data profiling in data cleaning and transformation. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  10574, s 480- 496 . doi: 10.1007/978-3-319-69459-7_32 Fulltekst i vitenarkiv. Vis sammendrag

  This paper proposes an approach for using visual data profiling in tabular data cleaning and transformation processes. Visual data profiling is the statistical assessment of datasets to identify and visualize potential quality issues. The proposed approach was implemented in a software prototype and empirically validated in a usability study to determine to what extent visual data profiling is useful and how easy it is to use by data scientists. The study involved 24 users in a comparative usability test and 4 expert reviewers in cognitive walkthroughs. The evaluation results show that users find visual data profiling capabilities to be useful and easy to use in the process of data cleaning and transformation.

• Pozzati, Stefano; Sanvito, Diego; Castelli, Claudio & Roman, Dumitru (2016). Understanding territorial distribution of Properties of Managers and Shareholders: a Data-driven Approach. Territorio Italia - Land Administration, Cadastre, Real Estate.  ISSN 2240-7707. . doi: 10.14609/Ti_2_16_2e
• Roman, Dumitru; Dimitrov, Marin; Nikolov, Nikolay; Pultier, Antoine; Elvesæter, Brian; Simov, Alex & Petkov, Yavor (2016). DataGraft: A Platform for Open Data Publishing. CEUR Workshop Proceedings.  ISSN 1613-0073.  1615 Fulltekst i vitenarkiv. Vis sammendrag

  DataGraft is a platform for Open Data management. It has the goals to simplify and speed up the data publishing process and to improve the reliability and scalability of the data consumption process. This demonstrator provides a summary of the key features of the current DataGraft platform as well as simple demo scenario from the domain of property-related data.

• Roman, Dumitru; Dimitrov, Marin; Nikolov, Nikolay; Pultier, Antoine; Sukhobok, Dina; Elvesæter, Brian; Berre, Arne- Jørgen; Ye, Xianglin; Simov, Alex & Petkov, Yavor (2016). DataGraft: Simplifying open data publishing. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  9989, s 101- 106 . doi: 10.1007/978-3-319-47602-5_21 Vis sammendrag

  In this demonstrator we introduce DataGraft – a platform for Open Data management. DataGraft provides data transformation, publishing and hosting capabilities that aim to simplify the data publishing lifecycle for data workers (i.e., Open Data publishers, Linked Data developers, data scientists). This demonstrator highlights the key features of DataGraft by exemplifying a data transformation and publishing use case with property-related data.

• Roman, Dumitru & Gatti, Stefano (2016). Towards a Reference Architecture for Trusted Data Marketplaces: The Credit Scoring Perspective, In Irfan Awan & Muhammad Younas (ed.),  2nd International Conference on Open and Big Data, (OBD) 2016, Vienna, Austria, August 22-24, 2016..  IEEE.  ISBN 978-1-5090-4054-4.  artikkel.  s 95 - 101 Vis sammendrag

  Data sharing presents extensive opportunities and challenges in domains such as the public sector, health care and financial services. This paper introduces the concept of "trusted data marketplaces" as a mechanism for enabling trusted sharing of data. It takes credit scoring-an essential mechanism of the entire world-economic environment, determining access for companies and individuals to credit and the terms under which credit is provisioned-as an example for the realization of the trusted data marketplaces concept. This paper looks at credit scoring from a data perspective, analyzing current shortcomings in the use and sharing of data for credit scoring, and outlining a conceptual framework in terms of a trusted data marketplace to overcome the identified shortcomings. The contribution of this paper is two-fold: (1) identify and discuss the core data issues that hinder innovation in credit scoring; (2) propose a conceptual architecture for trusted data marketplaces for credit scoring in order to serve as a reference architecture for the implementation of future credit scoring systems. The architecture is generic and can be adopted in other domains where data sharing is of high relevance.

• Sukhobok, Dina; Nikolov, Nikolay; Pultier, Antoine; Ye, Xianglin; Berre, Arne- Jørgen; Moynihan, Rick; Roberts, Bill; Elvesæter, Brian; Mahasivam, Nivethika & Roman, Dumitru (2016). Tabular data cleaning and linked data generation with grafterizer. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  9989, s 134- 139 . doi: 10.1007/978-3-319-47602-5_27 Vis sammendrag

  Over the past several years the amount of published open data has increased significantly. The majority of this is tabular data, that requires powerful and flexible approaches for data cleaning and preparation in order to convert it into Linked Data. This paper introduces Grafterizer – a software framework developed to support data workers and data developers in the process of converting raw tabular data into linked data. Its main components include Grafter, a powerful software library and DSL for data cleaning and RDF-ization, and Grafterizer, a user interface for interactive specification of data transformations along with a back-end for management and execution of data transformations. The proposed demonstration will focus on Grafterizer’s powerful features for data cleaning and RDF-ization in a scenario using data about the risk of failure of transport infrastructure components due to natural hazards.

• Vega-Gorgojo, Guillermo; Fjellheim, Roar; Roman, Dumitru; Akerkar, Rajendra & Waaler, Arild (2016). Big data in the oil & gas upstream industry - a case study on the Norwegian continental shelf. Oil, Gas.  ISSN 0342-5622.  42(II), s 67- 77 Vis sammendrag

  This case study is focused on the impact of big data in exploration and production of oil & gas in the Norwegian Continental Shelf. Overall, the industry is currently transitioning from mere data collection practices to more proactive uses of data, especially in the operations area. Positive economical impacts associated with the use of big data comprise data generation and data analytics business models, commercial partnerships around data, and the embracement of open data by the Norwegian regulator. On the negative side there are concerns regarding the future of existing business models and the reluctance of oil companies to share data. Positive social and ethical impacts include mitigation of safety and environment concerns with big data, personal privacy not really a problem, and creation of new jobs for data scientists; on the other hand cyberthreats are becoming a serious concern and there are trust issues with data.

• Archer, Phil; Charvat, Karel; Mariano Navarro, De La Cruz; Carlos Ángel, Iglesias; John, O'Flaherty; Tomás, Robles & Roman, Dumitru (2015). Linked Open Data for Environment Protection in Smart Regions - The SmartOpenData Project Approach. CEUR Workshop Proceedings.  ISSN 1613-0073.  1322 Vis sammendrag

  Many different open information sources currently exist for protecting the environment in Europe, mainly focused on Natura 2000 network, and areas where environmental protection and activities like tourism need to be balanced. Managing these data and integrating them for supporting decision makers and for novel uses is a challenging task. The SmartOpenData project (2013-1015) aims to define mechanisms for acquiring, adapting and using Open Data provided by existing sources for environment protection in European protected areas. Through target pilots in these areas, the project will harmonise metadata, improve spatial data fusion and visualisation and publish the resulting information according to user requirements and Linked Open Data principles to provide new opportunities for use. SmartOpenData will be based on previous experiences of Habitats project, which defined models and tools for managing spatial data in environmental protection areas. This paper provides an introduction to the SmartOpenData with a specific focus on the motivation, goals, and technical focus of the project, and outlines the architecture of the approach taken by SmartOpenData.

• Navarro, Mariano; Baiget, Ramon; Estrada, Jesus & Roman, Dumitru (2015). CAPAS: A Service for Improving the Assignments of Common Agriculture Policy Funds to Farmers and Land Owners. CEUR Workshop Proceedings.  ISSN 1613-0073.  1417 Vis sammendrag

  The Tragsa Group is part of the group of companies administered by the Spanish state-owned holding company Sociedad Estatal de Participaciones Industriales (SEPI). Its 37 years of experience have placed this business group at the forefront of different sectors ranging from agricultural, forestry, livestock, and rural development services, to conservation and protection of the environment in Spain. Tragsa is currently developing a business case around the implementation of a Common Agriculture Policy Assignment Service (CAPAS) – an extension of a currently active and widely used service (more than 20 million visits per year). The extension of the service in this business case is based on leveraging new cross-sectorial data sources, and targets a substantial reduction of incorrect agricultural funds assignments to farmers and land owners. This paper provides an overview of the business case, technical challenges related to the implementation of CAPAS (in areas such as data integration), discusses the current solution and potential use of rule technologies.

• Roman, Dumitru; Kopecký, Jacek; Vitvar, Tomas; Domingue, John & Fensel, Dieter (2015). WSMO-Lite and hRESTS: Lightweight semantic annotations for Web services and RESTful APIs. Journal of Web Semantics.  ISSN 1570-8268.  31, s 39- 58 . doi: 10.1016/j.websem.2014.11.006 Vis sammendrag

  Service-oriented computing has brought special attention to service description, especially in connection with semantic technologies. The expected proliferation of publicly accessible services can benefit greatly from tool support and automation, both of which are the focus of Semantic Web Service (SWS) frameworks that especially address service discovery, composition and execution. As the first SWS standard, in 2007 the World Wide Web Consortium produced a lightweight bottom-up specification called SAWSDL for adding semantic annotations to WSDL service descriptions. Building on SAWSDL, this article presents WSMO-Lite, a lightweight ontology of Web service semantics that distinguishes four semantic aspects of services: function, behavior, information model, and nonfunctional properties, which together form a basis for semantic automation. With the WSMO-Lite ontology, SAWSDL descriptions enable semantic automation beyond simple input/output matchmaking that is supported by SAWSDL itself. Further, to broaden the reach of WSMO-Lite and SAWSDL tools to the increasingly common RESTful services, the article adds hRESTS and MicroWSMO, two HTML microformats that mirror WSDL and SAWSDL in the documentation of RESTful services, enabling combining RESTful services with WSDL-based ones in a single semantic framework. To demonstrate the feasibility and versatility of this approach, the article presents common algorithms for Web service discovery and composition adapted to WSMO-Lite.

• Roman, Dumitru; Tertre, Francois; Llaves, Alejandro; Grcar, Miha; Skrjanc, Maja; Toma, Ioan; Pantazoglou, Michael; Trasca, Silviu; Bodsberg, Nils Rune & Borrebæk, Morten (2015). Enabling Access to Environmental Models, Data, and Services on the Web – Technical Results Summary from the ENVISION Project –. CEUR Workshop Proceedings.  ISSN 1613-0073.  1322 Vis sammendrag

  The Environmental Services Infrastructure with Ontologies (ENVISION) project (2010-2013) provided an IT infrastructure for non ICT-skilled users for semantic discovery and adaptive chaining and composition of environmental services. This paper summarizes the core results of the project with a focus on individual components, relevant stakeholders, and overall advancements made by the project.

• Shi, Ling; Pettersen, Bjørg E.; Østhassel, Ivar; Nikolov, Nikolay; Khorramhonarnama, Arash; Berre, Arne- Jørgen & Roman, Dumitru (2015). Norwegian state of estate: A reporting service for the state-owned properties in norway. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  9202, s 456- 464 . doi: 10.1007/978-3-319-21542-6_30 Vis sammendrag

  Statsbygg is the public sector administration company responsible for reporting the state-owned property data in Norway. Traditionally the reporting process has been resource-demanding and error-prone. The State of Estate (SoE) business case presented in this paper is creating a new reporting service by sharing, integrating and utilizing cross-sectorial property data, aiming to increase the transparency and accessibility of property data from public sectors enabling downstream innovation. This paper explains the ambitions of the SoE business case, highlights the technical challenges related to data integration and data quality, data sharing and analysis, discusses the current solution and potential use of rules technologies.

• Roman, Dumitru; Pop, Claudia Daniela; Roman, Roxana I.; Mathisen, Bjørn Magnus; Wienhofen, Leendert Wilhelmus Marinus; Elvesæter, Brian & Berre, Arne- Jørgen (2014). The Linked Data AppStore - A Software-as-a-Service Platform Prototype for Data Integration on the Web, In Rajendra Prasath; Philip O'Reilly & T. Kathirvalavakumar (ed.),  Mining Intelligence and Knowledge Exploration - Second International Conference, MIKE 2014, Cork, Ireland, December 10-12, 2014. Proceedings.  Springer.  ISBN 978-3-319-13816-9.  Artikkel.  s 382 - 396 Vis sammendrag

  This paper introduces The Linked Data AppStore (LD-AppStore) – a Software-as-a-Service platform prototype for data integration on the Web. Building upon emerging Linked Data technologies, the LD-AppStore targets data scientists/engineers (interested in simplifying tasks such as data cleaning, transformation, entity extraction, data visualization, crawling, etc.) as well as data integration tool developers (interested in exploiting the use of their tools by data engineers). This paper provides an overview of the architecture of the LD-AppStore, the APIs of the basic data operations supported by the platform, presents a set of data integration workflows, and discusses the current status of the implementation.

• Berre, Arne- Jørgen; Schade, Sven & Roman, Dumitru (2013). Environmental Infrastructures and Platforms with Citizens Observatories and Linked Open Data, In Jiří Hřebíček; Gerald Schimak; M. Kubásek & Andrea E. Rizzoli (ed.),  Environmental Software Systems. Fostering Information Sharing. 10th IFIP WG 5.11 International Symposium, ISESS 2013 Neusiedl am See, Austria, October 9-11, 2013. Proceedings.  Springer.  ISBN 978-3-642-41150-2.  Article.  s 688 - 696 Vis sammendrag

  A number of past and current research and development projects aim to improve the sharing and use of environmental information. In 2010, the Environmental Infrastructures and Platforms (ENVIP) initiative was introduced as a means to identify the European potentials and specify common building blocks (‘services and enablers’) related to these projects. Work began with a set of projects supporting the Shared Environmental Information System (SEIS). This paper briefly summarizes the ongoing result collection and introduces the next wave of activities, which will follow two newly emerging trends: Citizens Observatories and Linked Open Data. We invite interested parties and project consortia to provide their contributions for future analysis and synergies through the CEN/TC287 TR 15449-2 Best practices registry and the ENVIP initiative

• Roman, Dumitru; Bodsberg, Nils Rune & Tertre, Francois (2013). Enabling risk assessment of oil spills on coastlines: the ENVISION approach. Géosciences.  ISSN 1772-094X.  (17), s 65- 65
• Shi, Ling; Roman, Dumitru & Berre, Arne- Jørgen (2013). SBVR as a Semantic Hub for Integration of Heterogeneous Systems - A Case Study and Experience Report -. CEUR Workshop Proceedings.  ISSN 1613-0073.  1004 Vis sammendrag

  Extracting integration rules to handle semantic heterogeneity is one of the main challenges of achieving seamless connectivity between distributed systems. Semantics of Business Vocabulary and Rules (SBVR)’s machine and human readability and platform independence make it potentially suitable and interesting to study, as a central semantic hub of different systems. Semantic heterogeneity can be identified by comparing and analyzing vocabularies, fact models and business rules in the hub. Integration rules can then be extracted based on the semantic heterogeneity analysis. This article investigates and evaluates the usage of SBVR in heterogeneous systems integration. It provides a real- life case study and experience report on extracting integration rules based on an analysis of two Norwegian public sector’s heterogeneous IT-systems modeled in SBVR.

• Roman, Dumitru & Norheim, David (2012). An Overview of Norwegian Linked Open Data, In Jaime Lloret Mauri & Pascal Lorenz (ed.),  Proceedings of the Fourth International Conference on Information, Process, and Knowledge Management (eKNOW).  Xpert Publishing Services.  ISBN 978-1-61208-181-6.  article.  s 93 - 96 Vis sammendrag

  With Norway being one of the few countries outside of the English speaking world with a clear governmental strategy and commitment to open data, combined with one of the highest Internet penetration and mobile access in Europe, it offers interesting opportunities for becoming a great testbed for consuming Linked Open Data (LOD). With this paper we aim at presenting potential applications consuming Norwegian LOD and showing practical benefits of aggregating open data in highly sensitive domains for governments and the general public such as regional development and environmentally friendly behaviour. At the same time, this paper will serve as an overview of the Norwegian LOD as of mid 2011. The proposed applications will not only aim at demonstrating the benefits of the current Norwegian LOD, but will also make contributions to the improvement and extension of the existing data sets.

• Maué, Patrick & Roman, Dumitru (2011). The ENVISION Environmental Portal and Services Infrastructure. IFIP Advances in Information and Communication Technology.  ISSN 1868-4238.  359, s 280- 294 . doi: 10.1007/978-3-642-22285-6_31 Vis sammendrag

  The ENVISION Portal is a Web-enabled infrastructure for the discovery, annotation, and composition of environmental services. It is a tool to create Web sites dedicated to particular domain-specific scenarios such as oil spill drift modeling or landslide risk assessment. The underlying architecture based on pluggable user interface components is briefly discussed, followed by a presentation of the components resulting from the first iteration of the implementation. A walkthrough explains how to create a scenario website and populate it with the user interface components required for one specific scenario. The paper concludes with a discussion of open challenges identified during the implementation.

• Roman, Dumitru; Carrez, Cyril; Elvesæter, Brian & Berre, Arne- Jørgen (2011). Standards and Initiatives for Service Modeling - The Case of OMG SoaML, In Martin Zelm; Marten Van Sinderen; Guy Doumeingts & Potus Johnson (ed.),  Enterprise Interoperability : IWEI 2011 Proceedings, March 2011.  John Wiley & Sons.  ISBN 978-1-84821-317-3.  Artikkel.  s 137 - 146 Fulltekst i vitenarkiv. Vis sammendrag

  Service modeling is a key element of any service-oriented system. It is the foundation on which core service-related tasks such as service discovery, composition, and mediation rely. During the past years standardization bodies such as W3C, OMG and OASIS have been working on standardizing various aspects of services such as service functionalities, behavior, quality of services, etc. At the same time, initiatives from academia focused on developing ontologies and formal languages for specifying services. In this paper we give a brief overview of relevant initiatives and standardization activities in the area of service modeling, and, as an example of the use of such standards, guide the reader through the use of the OMG Service oriented architecture Modeling Language (SoaML) in a concrete service-oriented scenario in the manufacturing domain.

• Roman, Dumitru; Morin, Brice; Wang, Sixuan & Berre, Arne- Jørgen (2011). A Model-Driven Approach to Interoperability in B2B Data Exchange, In Martin Zelm; Marten Van Sinderen; Guy Doumeingts & Potus Johnson (ed.),  Enterprise Interoperability : IWEI 2011 Proceedings, March 2011.  John Wiley & Sons.  ISBN 978-1-84821-317-3.  Artikkel.  s 107 - 121 Fulltekst i vitenarkiv. Vis sammendrag

  With the B2B data exchange becoming ubiquitous nowadays, automating as much as possible the exchange of data between collaborative enterprise systems is a key requirement for ensuring agile interoperability and scalability in B2B collaborations. Semantic differences and inconsistencies between conceptual models of the exchanged B2B data hinder agility, and ultimately the interoperability in B2B collaborations. In this paper we introduce a model-driven technique and prototype that support humans in reconciling the differences between the data models of the parties involved in a data exchange, and enable a high degree of automation in the end-to-end data exchange process. Our approach is based on the use of OMG Model-Driven Architecture (MDA) for abstracting platform-specific schemas and instances to platform-independent metamodels and models, specification of transformations at the platform-independent level, and generation of executable mappings for run-time data exchange. This paper presents the MDA-based data exchange framework we have developed, and focuses on the mapping metamodel and the generation of executable mappings from platform-independent transformations. Benefits of the proposed framework include the possibility of the mappings creator to focus on the semantic, object-oriented model behind the different platformspecific schemas and specify the mappings at a more abstract, semantic level, with both specification and execution of data mappings (i.e. design- and run-time mapping) provided in a single, unifying framework.

• Roman, Dumitru; Schade, Sven & Berre, Arne- Jørgen (2011). Open Environmental Platforms: Top-Level Components and Relevant Standards. IFIP Advances in Information and Communication Technology.  ISSN 1868-4238.  359, s 217- 225 . doi: 10.1007/978-3-642-22285-6_24 Vis sammendrag

  We present our ideas of an open Information and Communication Technology (ICT) platform for monitoring, mapping and managing our environment. The envisioned solution bridges the gap between the Internet of Things, Content and Services, and highly specific applications, such as oil spill detection or marine monitoring. On the one hand, this environmental platform should be open to new technologies; on the other hand, it has to provide open standard interfaces to various application domains. We identify core components, standards, and needs for new standard development in ICT for environment. We briefly outline how our past and present activities contribute to the development of the desired open environmental platform. Future implementations shall contribute to sustainable developments in the environmental domain.

• Stuhr, Magnus; Roman, Dumitru & Norheim, David (2011). LODWheel – JavaScript-based Visualization of RDF Data. CEUR Workshop Proceedings.  ISSN 1613-0073.  782 Vis sammendrag

  Visualizing Resource Description Framework (RDF) data to support decision-making processes is an important and challenging aspect of consuming Linked Data. With the recent development of JavaScript libraries for data visualization, new opportunities for Web-based visualization of Linked Data arise. This paper presents an extensive evaluation of JavaScript-based libraries for visualizing RDF data. A set of criteria has been devised for the evaluation and 15 major JavaScript libraries have been analyzed against the criteria. The two JavaScript libraries with the highest score in the evaluation acted as the basis for developing LODWheel (Linked Open Data Wheel) – a prototype for visualizing Linked Open Data in graphs and charts – introduced in this paper. This way of visualizing RDF data leads to a great deal of challenges related to data-categorization and connecting data resources together in new ways, which are discussed in this paper.

• Wang, Sixuan; Morin, Brice; Roman, Dumitru & Berre, Arne- Jørgen (2011). A Semi-automatic approach Transformation approach for Semantic Interoperability, In  NATO Symposium and Workshop on Semantic & Domain Based Interoperability.  ..  ISBN 9789283701590.  artikkel. Fulltekst i vitenarkiv. Vis sammendrag

  As data exchange and model transformation become ubiquitous nowadays, it is a key requirement to improve interoperability of enterprise systems at the semantic level. Many approaches in Model-driven Architecture (MDA) and Model-driven Interoperability (MDI) emerge to fulfil the above requirement. However, most of them still demand significant user inputs and provide a low degree of automation, especially when it comes to finding the mappings. A generic approach that can easily handle both semantic interoperability and automatic transformation is currently missing. This paper presents AutoMapping, a semi-automatic model transformation architecture. This approach focuses on two aspects: 1) semi-automatic mapping between data models expressed as class diagrams by involving minimal user interactions at design-time; 2) generation of executable mappings. Particularly at design-time, a semantic engine that solves various kinds of semantic attribute mismatches is devised, such as type, scale, synonym, homonym, granularity, etc. Furthermore, a heuristic-based similarity analysis between each pair of classes is proposed, which takes all relations of classes into account, such as inheritance, reference, etc. Finally, a method is given to match fragments and then generate mappings specification that conforms the proposed mapping metamodel for solving existing semantic mismatches. The main contribution of this paper is to create a generic platform-independent approach for semi- automatic model transformation towards semantic interoperability, with tool-based implementation and motivating case experiment, showing the feasibility of using MDA and MDI techniques for semantic

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• Gutiérrez-Basulto, Víctor; Kliegr, Tomas; Soylu, Ahmet; Giese, Martin & Roman, Dumitru (ed.) (2020). Rules and Reasoning. 4th International Joint Conference, RuleML+RR 2020, Oslo, Norway, June 29 – July 1, 2020, Proceedings. Springer.  ISBN 978-3-030-57977-7.  187 s.
• Iglesias, Carlos A.; Roman, Dumitru; Roman, Dumitru & Dumitru, Roman (ed.) (2020). Intelligent Environments 2020. IOS Press.  ISBN 9781643680903.
• Fodor, Paul; Montali, Marco; Calvanese, Diego & Roman, Dumitru (ed.) (2019). Rules and Reasoning. Third International Joint Conference, RuleML+RR 2019. Bolzano, Italy, September 16–19, 2019. Proceedings.. Springer Nature.  ISBN 978-3-030-31094-3.  221 s.
• Benzmüller, Christoph; Ricca, Francesco; Parent, Xavier & Roman, Dumitru (ed.) (2018). Rules and Reasoning. Second International Joint Conference, RuleML+RR 2018, Luxembourg, Luxembourg, September 18–21, 2018, Proceedings.. Springer.  ISBN 978-3-319-99905-0.
• Panetto, Hervé; Debruyine, Christophe; Proper, Henderik A.; Ardagna, Claudio Agostino; Roman, Dumitru & Meersman, Robert (ed.) (2018). On the Move to Meaningful Internet Systems. OTM 2018 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2018, Valletta, Malta, October 22-26, 2018, Proceedings, Part I. Springer Nature.  ISBN 978-3-030-02609-7.
• Panetto, Hervé; Debruyne, Christophe; Proper, Henderik A.; Ardagna, Claudio Agostino; Roman, Dumitru & Meersman, Robert (ed.) (2018). On the Move to Meaningful Internet Systems. OTM 2018 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2018, Valletta, Malta, October 22-26, 2018, Proceedings, Part II. Springer Nature.  ISBN 978-3-030-02609-7.
• Costantini, Stefania; Enrico, Franconi; Van Woensel, William; Kontchakov, Roman; Sadri, Fariba & Roman, Dumitru (ed.) (2017). Rules and Reasoning International Joint Conference, RuleML+RR 2017, London, UK, July 12–15, 2017, Proceedings. Springer.  ISBN 978-3-319-61251-5.  239 s.
• Bassiliades, Nick; Fodor, Paul; Giurca, Adrian; Gottlob, Georg; Kliegr, Tomas; Nalepa, Grzegorz J.; Palmirani, Monica; Paschke, Adrian; Proctor, Mark; Roman, Dumitru; Sadri, Fariba & Stojanovic, Nenad (ed.) (2015). Proceedings of the RuleML 2015 Challenge, the Special Track on Rule-based Recommender Systems for the Web of Data, the Special Industry Track and the RuleML 2015 Doctoral Consortium hosted by the 9th International Web Rule Symposium (RuleML 2015). CEUR.  ISBN 000-0-000000-00-0.
• Bassiliades, Nick; Gottlob, Georg; Sadri, Fariba; Paschke, Adrian & Roman, Dumitru (ed.) (2015). Rule Technologies: Foundations, Tools, and Applications, 9th International Symposium, RuleML 2015, Berlin, Germany, August 2-5, 2015, Proceedings. Springer.  ISBN 978-3-319-21541-9.  472 s.
• Bikakis, Antonis; Fodor, Paul & Roman, Dumitru (ed.) (2014). Rules on the Web. From Theory to Applications - 8th International Symposium, RuleML 2014. Springer.  ISBN 978-3-319-09869-2.  338 s.

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• Roman, Dumitru; Alexiev, Vladimir; Paniagua, Javier; Elvesæter, Brian; Zernichow, Bjørn Marius von; Soylu, Ahmet; Simeonov, Boyan & Taggart, Chris (2020). A Bird’s-Eye View of euBusinessGraph: A Business Knowledge Graph for Company Data.
• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Martínez, Francisco Yedro; Kovacic, Matej; Posinkovic, Matej; Makgill, Ian; Taggart, Chris; Simperl, Elena; Lech, Till Christopher & Roman, Dumitru (2020). Integrating and Analysing Public Procurement Data through a Knowledge Graph: A Demonstration in a Nutshell.
• Soylu, Ahmet; Elvesæter, Brian; Turk, Philip; Lech, Till Christopher; Roman, Dumitru; Corcho, Oscar; Simperl, Elena & Konstantinidis, George (2019). Towards an Ontology for Public Procurement based on the Open Contracting Data Standard.
• Palmonari, Matteo; Roman, Dumitru; Cutrona, Vincenzo; Nikolov, Nikolay & Košmerlj, Aljaž (2019). Semantic Data Enrichment for Data Scientists.
• Palmonari, Matteo; Roman, Dumitru; Cutrona, Vincenzo; Nikolov, Nikolay & Košmerlj, Aljaž (ed.) (2019). Semantic Data Enrichment for Data Scientists: Tutorial website for the ESWC2019 tutorial on semantic data enrichment for data scientists.. Vis sammendrag

  The enrichment of a dataset with information coming from third-party data sources is a common data preparation task in data sci- ence. Semantic technologies and linked open data can provide valuable support for this task, paving the way for new data-scientist-friendly tools that may facilitate effort-consuming, difficult and boring data prepara- tion activities. In this tutorial, we will provide the audience with: an explanation of the role that semantics play in data enrichment for data science; a review of advantages and limitations of tools, methodologies and techniques for semantic data enrichment available today; a practical dive into the creation of data transformations for enriching the data and the usage of the enriched data to train predictive models. For the latter, we will use tools that support the interactive specification of data trans- formations and their scalable execution on large datasets and a use case where digital marketing data are enriched to weather-based predictive modeling.

• Turk, Philip; Soylu, Ahmet; Simperl, Elena; Corcho, Oscar; Grobelnik, Marko; Roman, Dumitru; Fernandez, Maria; Gatti, Stefano; Taggart, Chris; Skok Klima, Urška; Ferrari Uliana, Annie; Makgill, Ian & Lech, Till Christopher (2018). TheyBuyForYou: Enabling Procurement Data Value Chains.
• Costantini, Stefania; Franconi, Enrico; van Woensel, William; Kontchakov, Roman; Sadri, Fariba & Roman, Dumitru (2017). Preface. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  10364 LNCS, s V- VII
• Alferes, Josejulio; Bertossi, Leopoldo; Governatori, Guido; Fodor, Paul & Roman, Dumitru (2016). Preface. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  9718, s V- VII
• Bikakis, Antonis; Fodor, Paul & Roman, Dumitru (2014). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  8620 LNCS, s V- VI
• Roman, Dumitru (2014). DaPaaS – A Data and Platform as a Service Approach to Efficient Open Data Publication and Consumption.
• Roman, Dumitru (2014). DaPaaS - A Data- and Platform-as-a-Service Approach to Efficient Data Publication and Consumption.
• Roman, Dumitru (2014). Open Data Publication and Consumption - An Overview of Relevant Data Access Approaches and DaaS Solutions.
• Roman, Dumitru (2014). The DaPaaS Platform - Data-as-a-Service Solution for Open Data.
• Roman, Dumitru; Dimitrov, Marin; Roberts, Bill & Berre, Arne- Jørgen (2014). DaPaaS – A Data- and Platform-as-a-Service Approach to Efficient Open Data Publication and Consumption.
• Roman, Dumitru; Pop, Claudia D.; Roman, Roxana I.; Mathisen, Bjørn Magnus; Wienhofen, Leendert Wilhelmus Marinus; Elvesæter, Brian & Berre, Arne- Jørgen (2014). An Overview of the Linked Data AppStore.
• Fodor, Paul; Roman, Dumitru; Anicic, Darko; Wyner, Adam; Palmirani, Monica; Sottara, Davide & Lévy, François (2013). Joint Proceedings of the 7th International Rule Challenge, the Special Track on Human Language Technology and the 3rd RuleML Doctoral Consortium. CEUR Workshop Proceedings.  ISSN 1613-0073.  1004
• Roman, Dumitru (2013). Development of sensor-based Citizens‘ Observatory Community for improving quality of life in cities.
• Roman, Dumitru (2013). The BigIaS Platform: Simplifying Big Data Integration - A Software-as-a-Service Approach (Preliminary Analysis and Design).
• Roman, Dumitru (2013). UniLFS: A Unifying Logical Framework for Service Modeling and Contracting. Vis sammendrag

  This talk will present novel techniques for modeling and reasoning about service contracts with the help of Concurrent Transaction Logic and introduce a unifying framework called UniLFS — a Unifying Logical Framework for Service modeling and contracting. This framework significantly extends the modeling power of the previous works by allowing expressive data constraints and iterative processes in the specification of services. This approach not only captures typical procedural constructs found in established business process languages such as BPMN, but also greatly extends their functionality, enables declarative specification and reasoning about them, and opens a way for automatic generation of executable business processes from service contracts.

• Roman, Dumitru; Tertre, Francois; Llaves, Alejandro; Skrjanc, Maja; Toma, Ioan; Pantazoglou, Michael; Trasca, Silviu; Bodsberg, Nils Rune & Borrebæk, Morten (2013). Enabling Access to Environmental Models, Data, and Services on the Web – Technical Results Summary from the ENVISION Project –.
• Aït-Kaci, Hassan; Hu, Yuh-Jong; Nalepa, Grzegorz J.; Palmirani, Monica & Roman, Dumitru (2012). Proceedings of the RuleML2012@ECAI Challenge and Doctoral Consortium at the 6th International Symposium on Rules. CEUR Workshop Proceedings.  ISSN 1613-0073.  874
• Roman, Dumitru (2012). Consuming Norwegian Linked Open Data: Applications in Regional Development and Environmentally Friendly Behavior.
• Roman, Dumitru (2012). ENVISION project presentation.
• Roman, Dumitru (2012). Enabling Access to Environmental Models, Data, and Services on the Web.
• Roman, Dumitru (2012). Examples of Applications Consuming Norwegian Linked Open Data.
• Roman, Dumitru; Harth, Andreas & Grobelnik, Marko (2012). Big Linked Data.
• Roman, Dumitru (2011). Approaching the Future Internet.
• Roman, Dumitru; Gao, Xiaoxin & Berre, Arne- Jørgen (2011). Demonstration: Sensapp - An Application Development Platform for OGC-based Sensor Services. CEUR Workshop Proceedings.  ISSN 1613-0073.  839, s 107- 110 Vis sammendrag

  This paper introduces the Sensapp platform, a semantic and OGCbased sensor application platform to enable users to register, annotate, search, visualize, and compose OGC-based sensors and services for creating addedvalue services and applications. Functionalities of Sensapp such as sensor registration, sensor data visualization, visual composition and generation of executable service compositions are presented through the demo.

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