Dumitru Roman

• Simonet-Boulogne, Anthony; Solberg, Arnor; Sinaeepourfard, Amir; Roman, Dumitru; Perales, Fernando & Ledakis, Giannis [Vis alle 8 forfattere av denne artikkelen] (2022). Toward blockchain-based fog and edge computing for privacy-preserving smart cities. Frontiers in Sustainable Cities. 4. doi: 10.3389/frsc.2022.846987.
• Roman, Dumitru; Pultier, Antoine; Ma, Xiang; Soylu, Ahmet & Ulyashin, Alexander G. (2022). Data quality issues in solar panels installations: a case study. I Nguyen, Phu Hong; Magnanini, Maria Chiara & Sen, Sagar (Red.), Proceedings of the 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things (SEA4DQ 2022). Association for Computing Machinery (ACM). ISSN 978-1-4503-9459-8. s. 24–25. doi: 10.1145/3549037.3564120.
• Moen, Terje; Eidnes, Sølve; Stasik, Alexander Johannes; Hansen, Anders; Bouquet, Gregory & Pultier, Antoine [Vis alle 11 forfattere av denne artikkelen] (2022). Data quality issues for vibration sensors: a case study in ferrosilicon production. I Nguyen, Phu Hong; Magnanini, Maria Chiara & Sen, Sagar (Red.), Proceedings of the 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things (SEA4DQ 2022). Association for Computing Machinery (ACM). ISSN 978-1-4503-9459-8. doi: 10.1145/3549037.3561273.
• Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Roman, Dumitru & Soylu, Ahmet (2022). Evolution of Software Testing Strategies and Trends: Semantic Content Analysis of Software Research Corpus of the Last 40 Years. IEEE Access. ISSN 2169-3536. 10, s. 106093–106109. doi: 10.1109/ACCESS.2022.3211949.
• Thomas, Aleena; Nikolov, Nikolay; Pultier, Antoine; Roman, Dumitru; Elvesæter, Brian & Soylu, Ahmet (2022). SIM-PIPE DryRunner: An approach for testing container-based big data pipelines and generating simulation data. Computer Software and Applications Conference. ISSN 0730-3157. doi: 10.1109/COMPSAC54236.2022.00182. Vis sammendrag

  Big data pipelines are becoming increasingly vital in a wide range of data intensive application domains such as digital healthcare, telecommunication, and manufacturing for efficiently processing data. Data pipelines in such domains are complex and dynamic and involve a number of data processing steps that are deployed on heterogeneous computing resources under the realm of the Edge-Cloud paradigm. The processes of testing and simulating big data pipelines on heterogeneous resources need to be able to accurately represent this complexity. However, since big data processing is heavily resource-intensive, it makes testing and simulation based on historical execution data impractical. In this paper, we introduce the SIM - PIPE Dry Runner approach - a dry run approach that deploys a big data pipeline step by step in an isolated environment and executes it with sample data; this approach could be used for testing big data pipelines and realising practical simulations using existing simulators.

• Roman, Dumitru; Song, Hui; Loupos, Konstantinos; Krousarlis, Thomas; Soylu, Ahmet & Skarmeta, Antonio F. (2022). The Computing Fleet: Managing Microservices-based Applications on the Computing Continuum, 2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C). IEEE conference proceedings. ISSN 978-1-6654-9493-9. s. 40–44. doi: 10.1109/ICSA-C54293.2022.00015.
• Waszak, Maryna; Lam, An Ngoc; Hoffmann, Volker; Elvesæter, Brian; Mogos, Flavia Maria & Roman, Dumitru (2022). Let the Asset Decide: Digital Twins with Knowledge Graphs, 2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C). IEEE conference proceedings. ISSN 978-1-6654-9493-9. s. 35–39. doi: 10.1109/ICSA-C54293.2022.00014.
• Vetle, Ryen; Soylu, Ahmet & Roman, Dumitru (2022). Building Semantic Knowledge Graphs from (Semi-)Structured Data: A Review. Future Internet. ISSN 1999-5903. 14(5). doi: 10.3390/fi14050129. Fulltekst i vitenarkiv
• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Yedro Martínez, Francisco & Kovavic, Matej [Vis alle 13 forfattere av denne artikkelen] (2022). Data Quality Barriers for Transparency in Public Procurement. Information. ISSN 2078-2489. 13(2). doi: 10.3390/info13020099. Fulltekst i vitenarkiv
• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Blount, Tom & Yedro Martínez, Francisco [Vis alle 13 forfattere av denne artikkelen] (2022). TheyBuyForYou platform and knowledge graph: Expanding horizons in public procurement with open linked data. Semantic Web Journal. ISSN 1570-0844. 13(2), s. 265–291. doi: 10.3233/SW-210442. Fulltekst i vitenarkiv Vis sammendrag

  Public procurement is a large market affecting almost every organisation and individual; therefore, governments need to ensure its efficiency, transparency, and accountability, while creating healthy, competitive, and vibrant economies. In this context, open data initiatives and integration of data from multiple sources across national borders could transform the procurement market by such as lowering the barriers of entry for smaller suppliers and encouraging healthier competition, in particular by enabling cross-border bids. Increasingly more open data is published in the public sector; however, these are created and maintained in siloes and are not straightforward to reuse or maintain because of technical heterogeneity, lack of quality, insufficient metadata, or missing links to related domains. To this end, we developed an open linked data platform, called TheyBuyForYou, 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 advanced tools and services on top of the knowledge graph for anomaly detection, cross-lingual document search, and data storytelling. This article describes the TheyBuyForYou platform and knowledge graph, reports their adoption by different stakeholders and challenges and experiences we went through while creating them, and demonstrates the usefulness of Semantic Web and Linked Data technologies for enhancing public procurement.

• Roman, Dumitru; Alexiev, Vladimir; Paniagua, Javier; Elvesæter, Brian; Zernichow, Bjørn Marius von & Soylu, Ahmet [Vis alle 8 forfattere av denne artikkelen] (2022). The euBusinessGraph ontology: A lightweight ontology for harmonizing basic company information. Semantic Web Journal. ISSN 1570-0844. 13(1), s. 41–68. 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.

• Roman, Dumitru; Nikolov, Nikolay; Elvesæter, Brian; Soylu, Ahmet; Prodan, Radu & Kimovski, Dragi [Vis alle 17 forfattere av denne artikkelen] (2021). DataCloud: Enabling the Big Data Pipelines on the Computing Continuum. I Cherfi, Samira; Perini, Anna & Nurcan, Selmin (Red.), Research Challenges in Information Science: 15th International Conference, RCIS 2021, Limassol, Cyprus, May 11–14, 2021, Proceedings. Springer. ISSN 978-3-030-75017-6. s. 715–717. doi: 10.1007/978-3-030-75018-3. Fulltekst i vitenarkiv
• Matskin, Mihhail; Tahmasebi, Shirin; Layegh, Amirhossein; Payberah, Amir; Thomas, Aleena & Nikolov, Nikolay [Vis alle 7 forfattere av denne artikkelen] (2021). A Survey of Big Data Pipeline Orchestration Tools from the Perspective of the DataCloud Project. CEUR Workshop Proceedings. ISSN 1613-0073. s. 63–78. doi: 10.5281/zenodo.5910891.
• Roman, Dumitru; Nikolov, Nikolay; Soylu, Ahmet; Elvesæter, Brian; Song, Hui & Prodan, Radu [Vis alle 18 forfattere av denne artikkelen] (2021). Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview. Proceedings of the IEEE Symposium on Computers and Communications. ISSN 1530-1346. doi: 10.1109/ISCC53001.2021.9631410. Fulltekst i vitenarkiv Vis sammendrag

  Organisations possess and continuously generate huge amounts of static and stream data, especially with the proliferation of Internet of Things technologies. Collected but unused data, i.e., Dark Data, mean loss in value creation potential. In this respect, the concept of Computing Continuum extends the traditional more centralised Cloud Computing paradigm with Fog and Edge Computing in order to ensure low latency pre-processing and filtering close to the data sources. However, there are still major challenges to be addressed, in particular related to management of various phases of Big Data processing on the Computing Continuum. In this paper, we set forth an ecosystem for Big Data pipelines in the Computing Continuum and introduce five relevant real-life example use cases in the context of the proposed ecosystem.

• Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail & Payberah, Amir H. [Vis alle 7 forfattere av denne artikkelen] (2021). Big data workflows: Locality-aware orchestration using software containers. Sensors. ISSN 1424-8220. 21(24), s. 1–27. doi: 10.3390/s21248212. Fulltekst i vitenarkiv Vis sammendrag

  The emergence of the Edge computing paradigm has shifted data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructures. Therefore, data processing solutions must consider data locality to reduce the performance penalties from data transfers among remote data centres. Existing Big Data processing solutions provide limited support for handling data locality and are inefficient in processing small and frequent events specific to the Edge environments. This article proposes a novel architecture and a proof-of-concept implementation for software container-centric Big Data workflow orchestration that puts data locality at the forefront. The proposed solution considers the available data locality information, leverages long-lived containers to execute workflow steps, and handles the interaction with different data sources through containers. We compare the proposed solution with Argo Workflows and demonstrate a significant performance improvement in the execution speed for processing the same data units. Finally, we carry out experiments with the proposed solution under different configurations and analyze individual aspects affecting the performance of the overall solution.

• Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail & Payberah, Amir [Vis alle 7 forfattere av denne artikkelen] (2021). Locality-Aware Workflow Orchestration for Big Data. I Chbeir, Richard (Red.), MEDES '21: Proceedings of the 13th International Conference on Management of Digital EcoSystems. Association for Computing Machinery (ACM). ISSN 978-1-4503-8314-1. s. 62–70. doi: 10.1145/3444757.3485106. Fulltekst i vitenarkiv
• Parnas Gulnes, Maren; Soylu, Ahmet & Roman, Dumitru (2021). A graph-based approach for representing, integrating and analysing neuroscience data: the case of the murine basal ganglia. Data Technologies and Applications. ISSN 2514-9288. 56(3). doi: 10.1108/DTA-12-2020-0303. Fulltekst i vitenarkiv
• Nikolov, Nikolay; Dessalk, Yared Dejene; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail & Payberah, Amir [Vis alle 7 forfattere av denne artikkelen] (2021). Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers. nternet of Things: Engineering Cyber Physical Human Systems. ISSN 2542-6605. 16, s. 1–19. doi: 10.1016/j.iot.2021.100440. Fulltekst i vitenarkiv
• Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia & Soylu, Ahmet (2021). An Analysis of Data Production Based on the Consistency of Decision Matrices. Lecture Notes in Networks and Systems. ISSN 2367-3370. 307, s. 875–882. doi: 10.1007/978-3-030-85626-7_102. Fulltekst i vitenarkiv
• Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia & Soylu, Ahmet (2021). On Converting Crisp Failure Possibility into Probability for Reliability of Complex Systems. Lecture Notes in Networks and Systems. ISSN 2367-3370. 308, s. 622–629. doi: 10.1007/978-3-030-85577-2_73. Fulltekst i vitenarkiv
• Roman, Dumitru; Reeves, Neal; Gonzalez, Esteban; Celino, Irene; Abd El Kader, Shady & Turk, Philip Andreas [Vis alle 12 forfattere av denne artikkelen] (2021). An analysis of pollution Citizen Science projects from the perspective of Data Science and Open Science. Data Technologies and Applications. ISSN 2514-9288. 55(5), s. 622–642. doi: 10.1108/DTA-10-2020-0253. Fulltekst i vitenarkiv
• Sahin, Bekir; Yazidi, Anis; Roman, Dumitru & Soylu, Ahmet (2021). Ontology-Based Fault Tree Analysis Algorithms in a Fuzzy Environment for Autonomous Ships. IEEE Access. ISSN 2169-3536. 9, s. 1–18. doi: 10.1109/ACCESS.2021.3061929. Fulltekst i vitenarkiv
• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Martínez, Francisco Yedro & Kovacic, Matej [Vis alle 12 forfattere av denne artikkelen] (2020). Integrating and analysing public procurement data through a knowledge graph: A demonstration in a nutshell. CEUR Workshop Proceedings. ISSN 1613-0073. 2721(492), s. 34–38. Vis sammendrag

  This paper presents a demonstrator of a knowledge graph based approach for integrating and reconciling cross-border and cross-language procurement and company data from distributed data sources. The demonstrator also includes analysis of the resulting knowledge graph, exemplified in anomaly detection and cross-lingual search.

• Roman, Dumitru; Alexiev, Vladimir; Paniagua, Javier; Elvesæter, Brian; Zernichow, Bjørn Marius von & Soylu, Ahmet [Vis alle 8 forfattere av denne artikkelen] (2020). A Bird's-eye view of euBusinessGraph: A business knowledge graph for company data. CEUR Workshop Proceedings. ISSN 1613-0073. 2721(493), s. 39–43. Vis sammendrag

  This poster paper provides an overview of euBusinessGraph – a business knowledge graph for basic company data, together with related artefacts (datasets, ontology, and infrastructure), and its use for creating a prototype for a data marketplace for basic company data. euBusinessGraph was developed by aggregating, linking, and provisioning data from several distributed data sources.

• Roman, Dumitru & Soylu, Ahmet (2020). Enabling the European Business Knowledge Graph for Innovative Data-Driven Products and Services. ERCIM News. ISSN 0926-4981.
• Samuelsen, Simen; Nikolov, Nikolay; Soylu, Ahmet & Roman, Dumitru (2020). An Approach for Representing and Storing RDF Data in Multi-model Databases, 14th International Conference on Metadata and Semantics Research (MTSR 2020). Springer Nature. ISSN 978-3-030-36598-1.
• Abburu, Sailesh; Berre, Arne- Jørgen; Jacoby, Michael; Roman, Dumitru; Stojanovic, Ljiljana & Stojanovic, Nenad (2020). COGNITWIN – Hybrid and Cognitive Digital Twins for the Process Industry, 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-7037-4. s. 1–8. doi: 10.1109/ICE/ITMC49519.2020.9198403.
• Abburu, Sailesh; Berre, Arne J.; Jacoby, Michael; Roman, Dumitru; Stojanovic, Ljiljana & stojanovic, nenad (2020). Cognitive Digital Twins for the Process Industry. I Sennersten, Charlotte & Dini, Oana (Red.), COGNITIVE 2020, The Twelfth International Conference on Advanced Cognitive Technologies and Applications. Think Mind. ISSN 978-1-61208-780-1.
• Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Yedro Martínez, Francisco & Kovacic, Matej [Vis alle 12 forfattere av denne artikkelen] (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.

• Dessalk, Yared Dejene; Nikolov, Nikolay; Matskin, Mihhail; Soylu, Ahmet & Roman, Dumitru (2020). Scalable Execution of Big Data Workflows using Software Containers. I Chbeir, Richard; Manolopoulos, Yannis; Damiani, Ernesto & Benslimane, Djamal (Red.), MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems. ACM Publications. ISSN 978-1-4503-8115-4. s. 76–83. doi: 10.1145/3415958.3433082.
• Abd El Kader, Shady; Nikolov, Nikolay; Zernichow, Bjørn Marius von; Cutrona, Vincenzo; Palmonari, Matteo & Elvesæter, Brian [Vis alle 8 forfattere av denne artikkelen] (2019). Modeling and publishing French business register (SIRENE) data as linked data using the EubusinessGraph ontology. CEUR Workshop Proceedings. ISSN 1613-0073. 2549.
• 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. 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.

• 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: 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.

• Cutrona, Vincenzo; de Paoli, Flavio; Košmerlj, Aljaž; Nikolov, Nikolay; Palmonari, Matteo & Perales, Fernando [Vis alle 7 forfattere av denne artikkelen] (2019). Semantically-Enabled Optimization of Digital Marketing Campaigns. I Ghidini, Chiara; Hartig, Olaf; Maleshkova, Maria; Svátek, Vojtěch; Cruz, Isabel; Hogan, Aidan; Song, Jie; Lefrançois, Maxime & Gandon, Fabien (Red.), The Semantic Web – ISWC 2019. Springer. ISSN 978-3-030-30795-0. doi: 10.1007/978-3-030-30796-7_22.
• 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.

• 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
• Soylu, Ahmet; Elvesæter, Brian; Turk, Philip; Roman, Dumitru; Corcho, Oscar & Simperl, Elena [Vis alle 10 forfattere av denne artikkelen] (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.

• Soylu, Ahmet; Elvesæter, Brian; Turk, Philip; Roman, Dumitru; Corcho, Oscar & Simperl, Elena [Vis alle 8 forfattere av denne artikkelen] (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.

• Simperl, Elena; Corcho, Oscar; Grobelnik, Marko; Roman, Dumitru; Soylu, Ahmet & Ruíz, María Jesús Fernández [Vis alle 12 forfattere av denne artikkelen] (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
• Roman, Dumitru & Vu, Kien (2018). Enabling Data Markets Using Smart Contracts and Multi-party Computation. I Abramowicz, Witold & Paschke, Adrian (Red.), Business Information Systems Workshops. BIS 2018. . Springer. ISSN 978-3-030-04848-8. s. 258–263. doi: 10.1007/978-3-030-04849-5_23. Fulltekst i vitenarkiv
• Shi, Ling & Roman, Dumitru (2018). Ontologies for the Real Property Domain. I Akerkar, Rajendra (Red.), 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). ISSN 978-1-4503-5489-9. doi: 10.1145/3227609.3227661.
• Flouris, Giorgos; Patkos, Theodore; Chrysakis, Ioannis; Konstantinou, Ioulia; Nikolov, Nikolay & Papadakos, Panagiotis [Vis alle 10 forfattere av denne artikkelen] (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
• Simperl, Elena; Corcho, Oscar; Grobelnik, Marko; Roman, Dumitru; Soylu, Ahmet & Jesús Fernández Ruíz, María [Vis alle 12 forfattere av denne artikkelen] (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 [Vis alle 13 forfattere av denne artikkelen] (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.

• 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.

• Sukhobok, Dina; Nikolov, Nikolay & Roman, Dumitru (2017). Tabular Data Anomaly Patterns. I Younas, Muhammad; Awan, Irfan & Holubova, Irena (Red.), 2017 International Conference on Big Data Innovations and Applications (Innovate-Data), Prague, Czech Republic, Czech Republic, 21-23 Aug. 2017. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5386-0960-6. s. 25–34. doi: 10.1109/Innovate-Data.2017.10. Fulltekst i vitenarkiv
• Zernichow, Bjørn Marius von & Roman, Dumitru (2017). A Visual Data Profiling Tool for Data Preparation. I Bhulai, Sandjai & Kardaras, Dimitris (Red.), DATA ANALYTICS 2017 : International Conference on Data Analytics, Barcelona, Spain, November 12-16, 2017. International Academy, Research and Industry Association (IARIA). ISSN 978-1-61208-603-3. s. 12–14. Fulltekst i vitenarkiv
• Gan, Dennis Yong Chun & Roman, Dumitru (2017). MOBILE BIG DATA: THE SILVER BULLET FOR TELCOS? A CASE STUDY IN THE NORWEGIAN TELCOS MARKET. I Xiao, Yingcai & Abraham, Ajith P. (Red.), 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. ISSN 978-989-8533-66-1. s. 263–272. Fulltekst i vitenarkiv
• Roman, Dumitru; Kobernus, Michael John; Ødegård, Rune Åvar; Nikolov, Nikolay; Sukhobok, Dina & Zernichow, Bjørn Marius von [Vis alle 7 forfattere av denne artikkelen] (2017). ALaDIn: Shining a Light on Air Quality through Data Integration and Machine Learning. I Otjacques, Benoît; Hitzelberger, Patrik; Naumann, Stefan & Volker, Wohlgemuth (Red.), From Science to Society: The Bridge provided by Environmental Informatics, Adjunct Proceedings of the 31st EnviroInfo Conference, Luxembourg, September 13-15. 2017. Shaker Verlag. ISSN 978-3-8440-5495-8. s. 293–298.
• 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.

• 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. s. 11–35. doi: 10.14609/Ti_2_17_1e.
• 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.

• Roman, Dumitru; Paniagua, Javier; Tarasova, Tatiana; Georgiev, Georgi; Sukhobok, Dina & Nikolov, Nikolay [Vis alle 7 forfattere av denne artikkelen] (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.

• 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.

• 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.

• Sukhobok, Dina; Nikolov, Nikolay; Lech, Till Christopher; Moberg, Arnt-Henning; Frantsvåg, Roar & Bergaas, Helene Risti [Vis alle 7 forfattere av denne artikkelen] (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.

• 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 & 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.

• Nikolov, Nikolay; Sukhobok, Dina; Dragnev, Stefan; Dalgard, Steffen Harald; Elvesæter, Brian & Zernichow, Bjørn Marius von [Vis alle 7 forfattere av denne artikkelen] (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.

• 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.

• 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.

• 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.

• 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.

• Roman, Dumitru; Nikolov, Nikolay; Pultier, Antoine; Sukhobok, Dina; Elvesæter, Brian & Berre, Arne- Jørgen [Vis alle 17 forfattere av denne artikkelen] (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.

• 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 & Gatti, Stefano (2016). Towards a Reference Architecture for Trusted Data Marketplaces: The Credit Scoring Perspective. I Awan, Irfan & Younas, Muhammad (Red.), 2nd International Conference on Open and Big Data, (OBD) 2016, Vienna, Austria, August 22-24, 2016.. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5090-4054-4. s. 95–101. doi: 10.1109/OBD.2016.21.
• Roman, Dumitru; Dimitrov, Marin; Nikolov, Nikolay; Pultier, Antoine; Elvesæter, Brian & Simov, Alex [Vis alle 7 forfattere av denne artikkelen] (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 [Vis alle 10 forfattere av denne artikkelen] (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.

• Sukhobok, Dina; Nikolov, Nikolay; Pultier, Antoine; Ye, Xianglin; Berre, Arne- Jørgen & Moynihan, Rick [Vis alle 10 forfattere av denne artikkelen] (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.

• 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.

• Shi, Ling; Pettersen, Bjørg E.; Østhassel, Ivar; Nikolov, Nikolay; Khorramhonarnama, Arash & Berre, Arne- Jørgen [Vis alle 7 forfattere av denne artikkelen] (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.

• Archer, Phil; Charvat, Karel; Mariano Navarro, De La Cruz; Carlos Ángel, Iglesias; John, O'Flaherty & Tomás, Robles [Vis alle 7 forfattere av denne artikkelen] (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.

• 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 [Vis alle 10 forfattere av denne artikkelen] (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.

• Roman, Dumitru; Pop, Claudia D.; Roman, Roxana I.; Mathisen, Bjørn Magnus; Wienhofen, Leendert Wilhelmus Marinus & Elvesæter, Brian [Vis alle 7 forfattere av denne artikkelen] (2014). An Overview of the Linked Data AppStore. CEUR Workshop Proceedings. ISSN 1613-0073. 1312, s. 116–119. Fulltekst i vitenarkiv Vis sammendrag

  This demo/poster paper provides an overview of a Software-as-a-Service platform prototype for data integration on the Web – The Linked Data AppStore (LD-AppStore). It builds upon Linked Data technologies, targets data scientists/engineers and data integration application developers, and aims to provide a solution for simplifying tasks such as data transformation, querying, entity extraction, data visualization, crawling, etc. This paper focuses on the overall architecture of the LD-AppStore, basic data operations supported by the current prototype, and outlines the demonstration of the prototype.

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• Moschoyiannis, Sotiris; Penaloza Nyssen, Rafael; Vanthienen, Jan; Soylu, Ahmet & Roman, Dumitru (2021). Rules and Reasoning. 5th International Joint Conference, RuleML+RR 2021, Leuven, Belgium, September 8–15, 2021, Proceedings. Springer. ISBN 978-3-030-91166-9. 12851(1). 250 s.
• Iglesias, Carlos A.; Novella, Jose Ignacio Moreno; Ricci, Alessandro; Pinto, Diego Rivera & Roman, Dumitru (2020). Intelligent Environments 2020. IOS Press. ISBN 9781643680903. 442 s.
• Gutiérrez-Basulto, Víctor; Kliegr, Tomas; Soylu, Ahmet; Giese, Martin & Roman, Dumitru (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. 12173(1). 187 s.
• Fodor, Paul; Montali, Marco; Calvanese, Diego & Roman, Dumitru (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 (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; Debruyne, Christophe; Proper, Henderik A.; Ardagna, Claudio Agostino; Roman, Dumitru & Meersman, Robert (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.
• Panetto, Hervé; Debruyine, Christophe; Proper, Henderik A.; Ardagna, Claudio Agostino; Roman, Dumitru & Meersman, Robert (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.
• Costantini, Stefania; Enrico, Franconi; Van Woensel, William; Kontchakov, Roman; Sadri, Fariba & Roman, Dumitru (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; Gottlob, Georg; Sadri, Fariba; Paschke, Adrian & Roman, Dumitru (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. 9202(.). 472 s.
• Bassiliades, Nick; Fodor, Paul; Giurca, Adrian; Gottlob, Georg; Kliegr, Tomas & Nalepa, Grzegorz J. [Vis alle 12 forfattere av denne artikkelen] (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. 1417(.).

Se alle arbeider i Cristin

• Roman, Dumitru & Elvesæter, Brian (2022). Knowledge Graphs and Graphs Databases.
• Nystad, Erik Johan; Roman, Dumitru; Martin-Recuerda, Francisco & Waszak, Maryna (2022). Dashboard and Data Pipeline for Academic Network.
• Parnas Gulnes, Maren; Soylu, Ahmet & Roman, Dumitru (2021). Graph-based Management of Neuroscience Data: Representation, Integration and Analysis. ERCIM News. ISSN 0926-4981.
• Roman, Dumitru (2021). Forskere skal jakte på verdier i “mørke data”. [Fagblad]. Computerworld. Vis sammendrag

  Papir

• Gutiérrez-Basulto, Víctor; Soylu, Ahmet; Roman, Dumitru; Kliegr, Tomáš & Giese, Martin (2020). Preface. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 12173, s. v–vi.
• Fodor, Pál; Montali, Marco; Calvanese, Diego & Roman, Dumitru (2019). Preface. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11784 LNCS, s. 9–10. doi: 10.31826/9781463230111-001.
• Palmonari, Matteo; Roman, Dumitru; Cutrona, Vincenzo; Nikolov, Nikolay & Košmerlj, Aljaž (2019). Semantic Data Enrichment for Data Scientists: Tutorial website for the ESWC2019 tutorial on semantic data enrichment for data scientists.
• Palmonari, Matteo; Roman, Dumitru; Cutrona, Vincenzo; Nikolov, Nikolay & Košmerlj, Aljaž (2019). Semantic Data Enrichment for Data Scientists.
• Turk, Philip; Soylu, Ahmet; Simperl, Elena; Corcho, Oscar; Grobelnik, Marko & Roman, Dumitru [Vis alle 13 forfattere av denne artikkelen] (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; Dimitrov, Marin; Roberts, Bill & Berre, Arne- Jørgen (2014). DaPaaS – A Data- and Platform-as-a-Service Approach to Efficient Open Data Publication and Consumption.

Se alle arbeider i Cristin