• ACORDAR: A Test Collection for Ad Hoc Content-Based (RDF) Dataset Retrieval 

      Lin, Tengteng; Chen, Qiaosheng; Cheng, Gong; Soylu, Ahmet; Ell, Basil; Zhao, Ruoqi; Shi, Qing; Wang, Xiaxia; Gu, Yu; Kharlamov, Evgeny (IR: Research and Development in Information Retrieval;SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Conference object, 2022)
      Ad hoc dataset retrieval is a trending topic in IR research. Methods and systems are evolving from metadata-based to content-based ones which exploit the data itself for improving retrieval accuracy but thus far lack a ...
    • An Analysis of Data Production Based on the Consistency of Decision Matrices 

      Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia; Soylu, Ahmet (Lecture Notes in Networks and Systems;Volume 307, Peer reviewed; Journal article, 2021-08-24)
      Multi-criteria decision making methods are used to solve numerous problems related to several disciplines such as engineering, management and business. Consistency of a decision making application is of crucial importance ...
    • An analysis of pollution Citizen Science projects from the perspective of Data Science and Open Science 

      Roman, Dumitru; Reeves, Neal; Gonzalez, Esteban; Celino, Irene; Abd El Kader, Shady; Turk, Philip Andreas; Soylu, Ahmet; Corcho, Oscar; Cedazo, Raquel; Re Calegari, Gloria; Scandolari, Damiano; Simperl, Elena (Data Technologies and Applications;Volume 55 - Issue 5, Peer reviewed; Journal article, 2021-05-05)
      Purpose: Citizen Science – public participation in scientific projects – is becoming a global practice engaging volunteer participants, often non-scientists, with scientific research. Citizen Science is facing major ...
    • 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 (Proceedings of the IEEE Symposium on Computers and Communications;2021 IEEE Symposium on Computers and Communications (ISCC), Peer reviewed; Journal article, 2021-12-15)
      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 (Computer;Volume: 55, Issue: 11, Peer reviewed; Journal article, 2022-10-25)
      Big Data pipelines are essential for leveraging Dark Data, i.e., data collected but not used and turned into value. However, tapping their potential requires going beyond existing approaches and frameworks for Big Data ...
    • 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 (Sensors;Volume 21 / Issue 24, Peer reviewed; Journal article, 2021-12-08)
      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 ...
    • Building Semantic Knowledge Graphs from (Semi-)Structured Data: A Review 

      Vetle, Ryen; Soylu, Ahmet; Roman, Dumitru (Future Internet; Volume 14 / Issue 5, Peer reviewed; Journal article, 2022-04-24)
      Knowledge graphs have, for the past decade, been a hot topic both in public and private domains, typically used for large-scale integration and analysis of data using graph-based data models. One of the central concepts ...
    • Chrontext: Portable SPARQL queries over contextualised time series data in industrial settings 

      Bakken, Magnus; Soylu, Ahmet (Peer reviewed; Journal article, 2023)
      Industrial information models are standardised ways of representing industrial devices, equipment, and processes together with the data collected from associated sensors and control systems. Companies invest in such models ...
    • Comparative study of data transformation tools: An investigation of functionalities supported in common tools and case study of declarative and procedural data manipulation languages 

      Storvoll, Tine-Lovise (ACIT;2022, Master thesis, 2022)
      Today, organizations are collecting and storing huge amounts of data that could potentially be very valuable. Finding trends and patterns in historic data can allow businesses to make more informed decision. Data scientists ...
    • The Computing Fleet: Managing Microservices-based Applications on the Computing Continuum 

      Roman, Dumitru; Song, Hui; Loupos, Konstantinos; Krousarlis, Thomas; Soylu, Ahmet; Skarmeta, Antonio F. (IEEE International Conference on Software Architecture Workshops (ICSAW);2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), Conference object, 2022-05-25)
      In this paper we propose the concept of “Computing Fleet” as an abstract entity representing groups of heterogeneous, distributed, and dynamic infrastructure elements across the Computing Continuum (covering the Edge-Fog-Cloud ...
    • 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 (Internet of Things;Volume 16, December 2021, 100440, Peer reviewed; Journal article, 2021-11-26)
      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 ...
    • Container-Based Data Pipelines on the Computing Continuum for Remote Patient Monitoring 

      Nikolov, Nikolay Vladimirov; Solberg, Arnor; Prodan, Radu; Soylu, Ahmet; Matskin, Mihhail; Roman, Dumitru (Computer;, Peer reviewed; Journal article, 2023)
      Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedicine, especially in remote areas where direct interaction is hindered. Over the past three years, following the COVID-19 ...
    • ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER 

      Layegh, Amirhossein; Hossein Payberah, Amir; Soylu, Ahmet; Roman, Dumitru; Matskin, Mihhail (IEEE Annual International Computer Software and Applications Conference (COMPSAC);, Chapter; Peer reviewed; Conference object, 2023)
      Prompt-based language models have produced encouraging results in numerous applications, including Named Entity Recognition (NER) tasks. NER aims to identify entities in a sentence and provide their types. However, the ...
    • Data Quality Barriers for Transparency in Public Procurement 

      Soylu, Ahmet; Corcho, Oscar; Elvesæter, Brian; Badenes-Olmedo, Carlos; Yedro Martínez, Francisco; Kovavic, Matej; Posinkovic, Matej; Medvescek, Mitja; Makgill, Ian; Taggart, Chris; Simperl, Elena; Lech, Till Christopher; Roman, Dumitru (Information; Volume 13, Issue 2, Peer reviewed; Journal article, 2022-02-20)
      Governments need to be accountable and transparent for their public spending decisions in order to prevent losses through fraud and corruption as well as to build healthy and sustainable economies. Open data act as a major ...
    • Data quality issues in solar panels installations: a case study 

      Roman, Dumitru; Pultier, Antoine; Ma, Xiang; Soylu, Ahmet; Ulyashin, Alexander (SEA4DQ: Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things;SEA4DQ '22: 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things, Conference object, 2022-11-09)
      Solar photovoltaics (PV) is becoming an important source of global electricity generation. Modern PV installations come with a variety of sensors attached to them for monitoring purposes (e.g., maintenance, prediction of ...
    • 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 (Lecture Notes in Business Information Processing;Volume 415, Conference object, 2021-05)
      With the recent developments of Internet of Things (IoT) and cloud-based technologies, massive amounts of data are generated by heterogeneous sources and stored through dedicated cloud solutions. Often organizations generate ...
    • Datalog with External Machine Learning Functions for Automated Cloud Resource Configuration 

      Zheng, Zhuoxun; Savkovic, Ognjen; Phuc Luu, Huu; Soylu, Ahmet; Kharlamov, Evgeny; Zhou, Baifan (Peer reviewed; Journal article, 2023)
      Industry 4.0 and Internet of Things (IoT) technologies unlock unprecedented amount of data from factory production, posing big data challenges. In that context, distributed computing solutions such as cloud systems are ...
    • Enhancing Knowledge Graph Generation with Ontology Reshaping – Bosch Case 

      Zhou, Dongzhuoran; Zhou, Baifan; Zheng, Zhuoxun; Kostylev, Egor V.; Cheng, Gong; Jimenez-Ruiz, Ernesto; Soylu, Ahmet; Kharlamov, Evgeny (Lecture Notes in Computer Science (LNCS);Volume 13384, Peer reviewed; Journal article, 2022-07-20)
      In the context of Industry 4.0 and Internet of Things (IoT), modern manufacturing and production lines are equipped with software systems and sensors that constantly collect and send a high volume of data.
    • The euBusinessGraph Ontology: a Lightweight Ontology for Harmonizing Basic Company Information 

      Roman, Dumitru; Alexiev, Vladimir; Paniagua, Javier; Elvesæter, Brian; Zernichow, Bjørn Marius von; Soylu, Ahmet; Simeonov, Boyan; Taggart, Chris (Semantic Web Journal;Vol. 13, no. 1, Peer reviewed; Journal article, 2022-11-25)
      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 ...
    • Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch 

      Zheng, Zhuoxun; Zhou, Baifan; Zhou, Dongzhuoran; Soylu, Ahmet; Kharlamov, Evgeny (Chapter; Peer reviewed; Conference object, 2022)
      With the development of Industry 4.0 technology, modern industries such as Bosch’s welding monitoring witnessed the rapid widespread of machine learning (ML) based data analytical applications, which in the case of welding ...