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Present CFP : 2025 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The 27th International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP 2025), the premier workshop in this area, will take place co-located with EDBT 2025 in Barcelona (Spain) on March 25th 2025.
Submissions are now open at https://cmt3.research.microsoft.com/DOLAP2025 Official website: https://dolapworkshop.github.io/dolap-2025/ Abstract submission: November 29, 2024 Paper submission: December 6, 2024 Authors notification: January 22, 2025 Camera-ready: February 16, 2025 Workshop date: March 25, 2025 DOLAP accepts short and long paper submissions! Following the success of last year, this year we will invite extended abstracts for an interactive panel session on Federated and Distributed Data Spaces. As our consolidated tradition, the best papers presented at DOLAP will be invited to a special issue of Information Systems. Long papers include novel and mature research, industrial, or survey work. Long papers of good quality but not mature enough might be accepted to the workshop as short papers. Short papers include (ongoing) novel research works with preliminary results and vision/position papers outlining research issues for future work. Extended abstract will be invited to present in the interactive panel session, and include initial controversial ideas and visions, reports on early (or negative) results, or reflections on existing and future challenges on the theme of the interactive session. For instance: How are Data Spaces transforming traditional data management and analytics paradigms? How can we ensure data sovereignty and trust within Data Spaces while promoting data sharing and collaboration? How can we address the scalability and performance issues in querying and analyzing data across distributed Data Spaces? What are the implications of data analytics on Data Spaces for data privacy, security, and compliance with regulations like GDPR? What new opportunities and challenges do Data Spaces present for machine learning and AI applications? The panel session will feature short presentations followed by extensive and interactive discussions on the presented topics. We encourage the authors to propose topics and perspectives that will engage the audience and ignite debate among the participants. Ultimately, the goal is to tap into one of the original functions of workshops as a forum for discussion, where researchers come together to brainstorm and contribute to paving the way for future research directions. The page limit is 8 pages for full papers, 4 pages for short papers, and 2 pages for extended abstracts (in CEUR format, double-column, excluding references). Each submission will be reviewed by 3 members of the program committee, the review process is single-blind, and thus authors must include their names and affiliations in submissions. Extended abstracts are short papers with an abstract, a main body, and references but have only 2 standard pages of content references included. Research topics include, but are not limited to: Design and Language - Data management fundamentals: architectures, design, ETL/ELT, reverse ETL, modeling, data integration, database design for big data, query processing, maintenance, evolution, security, personalization, and privacy in decision support systems. - Data Variety: unstructured data (e.g., text), semi-structured data (e.g., XML, JSON), multimedia, spatial, temporal, and spatio-temporal data, stream and sensor data, semantic web, data lakes, data spaces, data quality, graph data, multistore and polystore solutions, multi-model data warehouse - Explainable, trustworthy, and interpretable analytics: bias in big data and how to mitigate it; data quality and data cleaning; FAIRness (Findability, Accessibility, Interoperability and Reusability) in OLAP Optimization - Coping with Volume: physical organization, performance optimization and tuning, scalability, MapReduce and Spark for data analytics, performance optimization of ETL/ELT. - Coping with Velocity: Deployment on parallel machine, database clusters, cloud infrastructures and serverless architectures, active/real-time analytics, real-time queries. Analytical Processing and Applications - Analytics and Value: OLAP, data exploration through visualization, recommendation, reformulation, approximate query-answering, personalization, result presentation, data storytelling, graph analytics, process mining, advanced visualization for business contexts. - Analytics and Veracity: heterogeneous data integration for analytics, quality aspects of data analysis, exploration outcome and end-user experience, fairness of data analysis, analytics and data driven decision making for the data enthusiasts. - Integration of analytics with machine learning, data mining, information retrieval, search engines, data science, predictive and prescriptive analytics. - Big Data applications: smart city, smart health, smart energy, smart grid, smart agriculture. === ## General Chair - Il-Yeol Song, Drexel University, United States ## Program co-Chairs Matteo Lissandrini, University of Verona, Italy Alejandro Maté, University of Alicante, Spain ## Steering Committee Alberto Abelló, Universitat Politecnica de Catalunya, Spain Ladjel Bellatreche, LIAS/ISAE-ENSMA, France Alfredo Cuzzocrea, Universitá della Calabria, Italy Enrico Gallinucci, Università di Bologna, Italy Carlos Garcia-Alvarado, Amazon, USA Lukasz Golab, University of Waterloo, Canada Matteo Golfarelli, University of Bologna, Italy Katja Hose, Aalborg University, Denmark Patrick Marcel, University of Orléans, France Carlos Ordonez, University of Houston, USA Torben Bach Pedersen, Aalborg University, Denmark Stefano Rizzi, University of Bologna, Italy Oscar Romero, Universitat Politecnica de Catalunya, Spain Alkis Simitsis, Athena Research Center, Greece Il-Yeol Song, Drexel University, USA Kostas Stefanidis, Tampere University, Finland Dimitri Theodoratos, New Jersey Institute of Technology, USA Juan Carlos Trujillo, University of Alicante, Spain Panos Vassiliadis, University of Ioannina, Greece Robert Wrembel, Poznan University of Technology, Poland Esteban Zimanyi, Universite Libre de Bruxelles, Belgium | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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