• Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview 

      Roman, Dumitru; Nikolov, Nikolay; Soylu, Ahmet; Elvesæter, Brian; Song, Hui; Prodan, Radu; Kimovski, Dragi; Marrella, Andrea; Leotta, Francesco; Matskin, Mihhail; Ledakis, Giannis; Theodosiou, Konstantinos; Simonet-Boulogne, Anthony; Perales, Fernando; Kharlamov, Evgeny; Ulisses, Alexandre; Solberg, Arnor; Ceccarelli, Raffaele (Peer reviewed; Journal article, 2021)
      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 ...
    • Big Data Pipelines on the Computing Continuum: Tapping the Dark Data 

      Roman, Dumitru; Prodan, Radu; Nikolov, Nikolay; Soylu, Ahmet; Matskin, Mihhail; Marrella, Andrea; Kimovski, Dragi; Elvesæter, Brian; Simonet-Boulogne, Anthony; Ledakis, Giannis; Song, Hui; Leotta, Francesco; Kharlamov, Evgeny (Peer reviewed; Journal article, 2022)
      The computing continuum enables new opportunities for managing big data pipelines concerning efficient management of heterogeneous and untrustworthy resources. We discuss the big data pipelines lifecycle on the computing ...
    • Big data workflows: Locality-aware orchestration using software containers 

      Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir H.; Roman, Dumitru (Peer reviewed; Journal article, 2021)
      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 ...
    • The cloud application modelling and execution language 

      Achilleos, Achilleas; Kritikos, Kyriakos; Rossini, Alessandro; Kapitsaki, Georgia; Domaschka, Jörg; Orzechowski, Michal; Seybold, Daniel; Griesinger, Frank; Nikolov, Nikolay; Romero, Daniel; Papadopoulos, George A. (Peer reviewed; Journal article, 2019)
      Cloud computing offers a flexible pay-as-you-go model for provisioning application resources, which enables applications to scale on-demand based on the current workload. In many cases, though, users face the single vendor ...
    • Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers 

      Nikolov, Nikolay; Dessalk, Yared Dejene; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir; Roman, Dumitru (Peer reviewed; Journal article, 2021)
      Big Data processing, especially with the increasing proliferation of Internet of Things (IoT) technologies and convergence of IoT, edge and cloud computing technologies, involves handling massive and complex data sets on ...
    • Data preparation as a service based on Apache Spark 

      Mahasivam, Nivethika; Nikolov, Nikolay; Sukhobok, Dina; Roman, Dumitru (Journal article; Peer reviewed, 2017)
      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 ...
    • The Data Value Quest: A Holistic Semantic Approach at Bosch 

      Zhou, Baifan; Zheng, Zhuoxun; Zhou, Dongzhuoran; Cheng, Gong; Jimenez-Ruiz, Ernesto; Trung-Kien, Tran; Stepanova, Daria; Gad-Elrab, Mohamed H.; Nikolov, Nikolay; Soylu, Ahmet; Kharlamov, Evgeny (Peer reviewed; Journal article, 2022)
    • DataCloud: Enabling the Big Data Pipelines on the Computing Continuum 

      Roman, Dumitru; Nikolov, Nikolay; Elvesæter, Brian; Soylu, Ahmet; Prodan, Radu; Kimovski, Dragi; Marrella, Andrea; Leotta, Francesco; Benvenuti, Dario; Matskin, Mihhail; Ledakis, Giannis; Simonet-Boulogne, Anthony; Perales, Fernando; Kharlamov, Evgeny; Ulisses, Alexandre; Solberg, Arnor; Ceccarelli, Raffaele (Chapter, 2021)
    • DataGraft beta v2: New features and capabilities 

      Nikolov, Nikolay; Sukhobok, Dina; Dragnev, Stefan; Dalgard, Steffen Harald; Elvesæter, Brian; von Zernichow, Bjørn Marius; Roman, Dumitru (Journal article; Peer reviewed, 2017)
      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, ...
    • DataGraft: A Platform for Open Data Publishing 

      Roman, Dumitru; Dimitrov, Marin; Nikolov, Nikolay; Pultier, Antoine; Elvesæter, Brian; Simov, Alex; Petkov, Yavor (Journal article; Peer reviewed, 2016)
      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 ...
    • Interacting with subterranean infrastructure linked data using augmented reality 

      Sukhobok, Dina; Nikolov, Nikolay; Lech, Till Christopher; Moberg, Arnt-Henning; Frantsvåg, Roar; Bergaas, Helene Risti; Roman, Dumitru (Journal article; Peer reviewed, 2017)
      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 ...
    • Linked data for the Norwegian state of estate reporting service 

      Shi, Ling; Pettersen, Bjørg Elsa; Sukhobok, Dina; Nikolov, Nikolay; Roman, Dumitru (Journal article; Peer reviewed, 2017)
      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 ...
    • Locality-Aware Workflow Orchestration for Big Data 

      Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir; Roman, Dumitru (Chapter; Peer reviewed, 2021)
      The development of the Edge computing paradigm shifts data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructure. Such a paradigm requires data processing solutions that ...
    • Norwegian State of estate report as linked open data 

      Shi, Ling; Sukhobok, Dina; Nikolov, Nikolay; Roman, Dumitru (Journal article; Peer reviewed, 2017)
      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 ...
    • ProDataMarket: A data marketplace for monetizing linked data 

      Roman, Dumitru; Paniagua, Javier; Tarasova, Tatiana; Georgiev, Georgi; Sukhobok, Dina; Nikolov, Nikolay; Lech, Till Christopher (Journal article; Peer reviewed, 2017)
      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 ...
    • SIM-PIPE DryRunner: An approach for testing container-based big data pipelines and generating simulation data 

      Thomas, Aleena; Nikolov, Nikolay; Pultier, Antoine; Roman, Dumitru; Elvesæter, Brian; Soylu, Ahmet (Peer reviewed; Journal article, 2022)
      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 ...
    • Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines 

      Khan, Akif Quddus; Nikolov, Nikolay; Matskin, Minhail; Prodan, Radu; Roman, Dumitru; Sahin, Bekir; Bussler, Christoph; Soylu, Ahmet (Peer reviewed; Journal article, 2023)
      Big data pipelines are developed to process data characterized by one or more of the three big data features, commonly known as the three Vs (volume, velocity, and variety), through a series of steps (e.g., extract, ...
    • Tabular Data Anomaly Patterns 

      Sukhobok, Dina; Nikolov, Nikolay; Roman, Dumitru (Chapter, 2017)
      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 ...
    • The InfraRisk ontology: enabling semantic interoperability for critical infrastructures at risk from natural hazards 

      Roman, Dumitru; Sukhobok, Dina; Nikolov, Nikolay; Elvesæter, Brian; Pultier, Antoine (Journal article; Peer reviewed, 2017)
      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 ...
    • Towards a collective awareness platform for privacy concerns and expectations 

      Flouris, Giorgos; Patkos, Theodore; Chrysakis, Ioannis; Konstantinou, Ioulia; Nikolov, Nikolay; Papadakos, Panagiotis; Pitt, Jeremy; Roman, Dumitru; Stan, Alexandru; Zeginis, Chrysostomos (Journal article; Peer reviewed, 2018)
      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, ...