Program

Day 1 (July 3rd, 2025)
Time Event
8:00 - 8:30am Registration
8:30 - 10:00am Session 1: "Graphs & Knowledge Management"
Chair: Yannis Vassiliou
8:30 - 8:48am
Danae Pla Karidi (Archimedes, Athena Research Center)*; Evaggelia Pitoura (University of Ioannina and Archimedes, Athena Research Center)

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8:48 - 9:06am Haridimos Kondylakis (FORTH-ICS & Computer Science Department, University of Crete)*

Click to display the abstract Abstract: The exact evaluation of queries over knowledge graphs encoded as RDF data has been extensively studied. However, in a wide array of applications, RDF queries do not even terminate, due to performance reasons. Notably, queries on public SPARQL endpoints are oftentimes timed out without returning any results. To address this, we propose a novel solution to the problem of progressive query answering and introduce the PING system that implements it on top of SPARK. In our approach, graph query answering leverages a hierarchical structure, which facilitates effective data partitioning, thus allowing us to reduce the sizes of intermediate results and return progressive answers. Moreover, it allows the RDF query evaluation algorithms to directly locate and access the different hierarchy levels required for query answering. Navigating through the hierarchy levels allows expanding or shrinking query results at different granularities. The extensive experimental study on real-world graph datasets, with varied query workloads, shows PING’s effectiveness and efficiency, on both exact and progressive query answering, and its superiority to the most relevant baselines.

9:06 - 9:24am
Evangelia Tsoukanara (University of Macedonia); Georgia Koloniari (University of Macedonia)*; Evaggelia Pitoura (University of Ioannina); Peter Triantafillou (University of Warwick)

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9:24 - 9:42am
Panos Vassiliadis (University of Ioannina ); Alexandros Karakasidis (University of Macedonia)*

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9:42 - 10:00am
guozhong Li (KAUST); Muhannad Alhumaidi (KAUST)*; Spiros Skiadopoulos (UOP); Ibrahim Hoteit (KAUST); Panos Kalnis (KAUST)

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10:00 - 10:30am Coffee Break
10:30 - 12:00pm Session 2: "Systems"
Chair: Panos Chrysanthis
10:30 - 10:48am
Xenofon Chatziliadis (Technische Universität Berlin)*; Eleni Tzirita Zacharatou (Hasso Plattner Institute); Alphan Eracar (Technische Universität Berlin); Steffen Zeuch (Technische Universität Berlin); Volker Markl (Technische Universität Berlin)

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10:48 - 11:06am
Edson Ramiro Lucas Filho (Cyprus University of Technology); George Savva (Cyprus University of Technology); Lun Yang (Huawei Technologies Co., Ltd.); Kebo Fu (Huawei Technologies Co., Ltd.); Jianqiang Shen (Huawei Technologies Co., Ltd.); Herodotos Herodotou (Cyprus University of Technology)*

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11:06 - 11:24am
Haralampos Gavriilidis (Technische Universität Berlin)*; Kaustubh Beedkar (Indian Institute of Technology Delhi); Matthias Boehm (BIFOLD and Technische Universität Berlin); Volker Markl (BIFOLD, Technische Universität Berlin, and DFKI GmbH)

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11:24 - 11:42am
Antonios Katsarakis (Huawei Research)*; Vasilis Gavrielatos (Huawei Research); Chris Jensen (University of Cambridge); Nikos Ntarmos (Huawei Research, Edinburgh)

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11:42 - 12:00pm
Mahesh Dananjaya (Huawei Research, Edinburgh); Vasilis Gavrielatos (Huawei Research, Edinburgh); Antonios Katsarakis (Huawei Research)*; Nikos Ntarmos (Huawei Research, Edinburgh); Vijay Nagarajan (University of Utah)

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12:00pm - 1:00pm Keynote: Mosaics in Big Data
Prof. Dr. Volker Markl (TU Berlin, Germany)
Click to display the abstract Abstract: Data management systems research focuses on improving human and technical efficiency for performing data analysis tasks. In this presentation, I describe selected research contributions to achieve that goal. I first highlight work on using query feedback in order to improve the cardinality model of a relational query optimizer. I then will discuss how the research vision of the Stratosphere research project at TU Berlin lead to the creation of the data stream processing system Apache Flink. As a third contribution, I will discuss how fractal space-filling curves can be used to efficiently process multidimensional range queries. I will conclude by giving an outlook on NebulaStream, a novel data processing system to handle massively distributed data streams on heterogeneous devices.

1:00 - 2:00pm Lunch Break
2:00 - 3:30pm Session 3: "Spatial, Time-series & Scientific"
Chair: George Papastefanatos
2:00 - 2:18pm
Dimitrios Giouroukis (BIFOLD, TU Berlin)*; Varun Pandey (BIFOLD, TU Berlin); Steffen Zeuch (BIFOLD, TU Berlin); Volker Markl (BIFOLD, TU Berlin)

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2:18 - 2:36pm Fatemeh Zardbani (Aarhus University); Konstantinos Lampropoulos (University of Ioannina); Nikos Mamoulis (University of Ioannina); Panagiotis Karras (University of Copenhagen)*

Click to display the abstract Abstract: Adaptive indexing allows for the progressive and simultaneous query-driven exploration and indexing of memory-resident data, starting as soon as they become available without upfront indexing. This technique has been so far applied to one-dimensional and multidimensional data, as well as to objects with spatial extent arising in geographic information systems. However, existing spatial adaptive indexing methods cater to static data made available in an one-off manner. To date, no spatial adaptive indexing method can ingest data updates interleaved with data exploration. In this paper we introduce GLIDE, a novel method that intertwines the adaptive indexing and incremental updating of a spatial-object data set. GLIDE builds a hierarchical spatial index incrementally in response to queries and also ingests updates judiciously into it. We examine several design choices and settle for a variant that combines gradual self-driven top-down insertions with query-driven indexing operations. In an extensive experimental comparison, we show that GLIDE achieves a lower cumulative cost than upfront-indexing methods and adaptive-indexing baselines.
2:36 - 2:54pm
Xenophon Kitsios (Athens University of Economics and Business)*; Panagiotis Liakos (Athens University of Economics and Business); Katia Papakonstantinopoulou (Athens University of Economics and Business); Yannis Kotidis (Athens University of Economics and Business)

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2:54 - 3:12pm Achilleas Michalopoulos (University of Ioannina); Dimitrios Tsitsigkos (Archimedes, Athena Research Center); Panagiotis Bouros ( Johannes Gutenberg Universitat Mainz); Nikos Mamoulis (University of Ioannina)*; Manolis Terrovitis (IMSI, Athena Research Center)

Click to display the abstract Abstract: Distance queries, including distance-range queries, k-nearest neighbors search, and distance joins, are very popular in spatial databases. However, they have been studied mainly for point data. Inspired by a recent approach on indexing non-point objects for rectangular range queries, we propose a secondary partitioning approach for space-partitioning indices, which is appropriate for distance queries. Our approach classifies the contents of each primary partition into 16 secondary partitions, taking into consideration the begin and end values of objects with respect to the spatial extent of the primary partition. Based on this, we define algorithms for three popular spatial query types, that avoid duplicate results and skip unnecessary computations. We compare our approach to the previous secondary partitioning method and to state-of-the-art data-partitioning indexing and find that it has a significant performance advantage.

3:12 - 3:30pm Nikolaos Koutroumanis (Archimedes, Athena Research Center)*; Christos Doulkeridis (University of Piraeus); Akrivi Vlachou (Department of Information and Communication Systems Engineering)

Click to display the abstract Abstract: Parallel spatial join algorithms are essential for scalable processing and analysis of big spatial data. The state-of-the-art algorithms rely on splitting the data into partitions and replicating objects from one data set in neighboring partitions, so that partitions can be processed in parallel independently without producing duplicate results. However, this universal replication of one data set leads to suboptimal performance in the case of skewed data sets with varying density. Instead, we advocate an approach that adaptively selects which data set to replicate in different local areas of the space, thus minimizing replication and boosting the performance of query processing. To this end, we contrive a graph-based framework for modeling replication between neighboring partitions. We study the theoretical properties that lead to adaptive replication with correct and duplicate-free results. Then, we design a data-parallel algorithm in Apache Spark which is based on adaptive replication, and we demonstrate its performance gain over the state-of-the-art for large-sized data sets, real and synthetic, under various settings.

3:30 - 4:00pm Coffee break
4:00 - 4:54pm Session 4a: "Lightning Talks Demo, Research Poster & Student Poster"
4:00 - 4:03pm Fan Yang (The Ohio State University); John Paparrizos (The Ohio State University)*

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4:03 - 4:06pm
Jens d'Hondt (TU Eindhoven); Haojun Li (The Ohio State University); Fan Yang (The Ohio State University); Odysseas Papapetrou (TU Eindhoven); John Paparrizos (The Ohio State University)*

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4:06 - 4:09pm
Tiago Brasileiro Araujo (Tampere University); Vasilis Efthymiou (Harokopio University of Athens); Vassilis Christophides (ENSEA, ETIS); Evaggelia Pitoura (University of Ioannina); Kostas Stefanidis (Tampere University)*

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4:09 - 4:12pm
"Mike Xydas (Athena Research Center)*; Anna Mitsopoulou (Athena Research Center ); George Katsogiannis-Meimarakis (Athena Research Center ); Chris Tsapelas (Athena Research Center ); Stavroula Eleftherakis (Athena Research Center); Αntonis Μandamadiotis (Athena Research Center ); Georgia Koutrika (Athena Research Center)"

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4:12 - 4:15pm
Christos Balaktsis (Aristotle University of Thessaloniki)*; Ioannis Mavroudopoulos (Aristotle University of Thessaloniki); Marco Comuzzi (Ulsan National Institute of Science and Technology); Anastasios Gounaris (Aristotle University of Thessaloniki); Fabrizio Maggi (Free University of Bozen-Bolzano)

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4:15 - 4:18pm
Konstantin Krasovitskiy (University of Cyprus); Stelios Christou (University of Cyprus); Demetris Zeinalipour (University of Cyprus)*

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4:26 - 4:21pm
Yannis Foufoulas (Athena Research Center)*; Theoni Palaiologou (University of Athens); Alkis Simitsis (Athena Research Center)

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4:21 - 4:24pm
Aryan Esmailpour (University of Illinois Chicago); Sainyam Galhotra (Cornell University); Rahul Raychaudhury (Duke University); Stavros Sintos (University of Illinois Chicago)*

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4:24 - 4:27pm
Georgios Grigoropoulos (Kpler)*; Alexandros Troupiotis - Kapeliaris (Kpler); Ilias Chamatidis (Kpler); Evangelia Filippou (Kpler); Konstantina Bereta (Kpler)

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4:27 - 4:30pm
Pantelis Ypsilantis (Aristotle University Of Thessaloniki); Theodoros Toliopoulos (Aristotle University of Thessaloniki)*; Anastasios Gounaris (Aristotle University Of Thessaloniki)

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4:30 - 4:33pm
Andreas Doumouras (University of the Peloponnese); Evangelos Mitikas (University of West Attica); Ermis Doulos (University of the Peloponnese); Manos Schoinoplokakis (University of the Peloponnese); Giannis Nikolentzos (University of the Peloponnese); Christos Tryfonopoulos (University of the Peloponnese)*; Spiros Skiadopoulos (University of the Peloponnese); Costas Vassilakis (University of the Peloponnese); Paraskevi Raftopoulou (University of the Peloponnese)

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4:33 - 4:36pm
Styliani Kyrama (Aristotle University of Thessaloniki)*; Anastasios Gounaris (Aristotle University of Thessaloniki)

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4:36 - 4:39pm
George Balanos (University of Ioannina)*

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4:39 - 4:42pm
"Thanasis Georgiadis (University of Ioannina)*; Achilleas Michalopoulos (University of Ioannina); Dimitris Dimitropoulos ( University of Ioannina); Dimitris Tsitsigkos (Archimedes, AthenaRC); Nikos Mamoulis (University of Ioannina)"

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4:42 - 4:45pm
Evangelos Chasanis (Archimedes Unit, Athena Research Center)*

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4:45 - 4:48pm
Theodora Troizi (Athena Research Center)*; Ioannis Foufoulas (Athena Research Center); Alkis Simitsis (Athena Research Center)

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4:48 - 4:51pm
Pavlos Spanoudakis (Athena Research Center)*; Ioannis Foufoulas (Athena Research Center); Alkis Simitsis (Athena Research Center)

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4:51 - 4:54pm
Georgios-Alexandros Kostas (University of Athens)*; Ioannis Xiros (University of Athens); Zisimos Vakras (University of Athens)

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5:00 - 6:00pm Session 4b: "Demo, Research Poster & Student Poster Presentations"
9:00-10:30pm Social Dinner


Day 2 (July 4th, 2025)
Time Event
8:30 - 10:00am Session 5: "Query Processing and Language Interfaces"
Chair: Haridimos Kondylakis
8:30 - 8:48am
Konstantin Krasovitskiy (University of Cyprus); Stelios Christou (University of Cyprus); Demetris Zeinalipour (University of Cyprus)*; test test (test)

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8:48 - 9:06am Apostolos Mavrogiannakis (UCSC)*; Xian Wang (HKUST); Ioannis Demertzis (UCSC); Dimitrios Papadopoulos (HKUST); Minos Garofalakis (Athena Research Center)

Click to display the abstract Abstract: We introduce oblivious parallel operators designed for both non-foreign key and foreign key equi-joins. Obliviousness ensures nothing is revealed about the data besides input/output sizes, even against a strong adversary that can observe memory access patterns. Our solution achieves this by combining trusted hardware with efficient oblivious primitives for compaction and sorting, and two oblivious algorithms: (i) an oblivious aggregation tree, which can be described as a variation of the parallel prefix sum, customized for trusted hardware, and (ii) a novel algorithm for obliviously expanding the elements of a relation. In the sequential setting, our oblivious join performs 4.6×- 5.14× faster than the prior state-of-the-art solution (Krastnikov et al., VLDB 2020) on data sets of size n = 2^24. In the parallel setting, our algorithm achieves a speedup of up to roughly 16× over the sequential version, when running with 32 threads (becoming up to 80× compared to the sequential algorithm of Krastnikov et al.). Finally, our oblivious operators can be used independently to support other oblivious relational database queries, such as oblivious selection and oblivious group-by.

9:06 - 9:24am George Konstantinidis (University of Southampton)*

Click to display the abstract Abstract: Bag-semantics allows for atomic relations and query answers to contain multiple copies of the same data tuple, reflecting real-world database systems more accurately. Deciding containment under bag-semantics (or simply, bag-containment) for two conjunctive queries (CQs) requires determining whether the answer of the first query, taking multiplicities into account, is contained within the answer of the second query, across all databases. Despite numerous attempts in the last thirty years, this problem of determining decidability and complexity of this task remains open as one of the prominent challenges in database theory, given its relevance in important applications. Previous works have established the decidability of the problem for specific classes of queries, among which is the the bag-containment of projection-free queries (PFQs), i.e., queries without existentially quantified variables, into general CQs. In this work, we push the boundaries further by addressing a broader, yet natural, fragment of CQs, called join-on free queries (JoFQ), which allows existential variables, while prohibiting joins involving them. We prove decidability of bag-containment of a JoFQ within a general CQ, placing the complexity of the problem in the first non-deterministic layer of the exponential hierarchy. The approach involves a homomorphism-counting reduction to the solution of a system of Diophantine inequalities with a specific structure (an undecidable problem in its general form) and an algorithm designed to address this category of inequalities.

9:24 - 9:42am
Christos Papadopoulos (Aalborg University)*; Alkis Simitsis (Athena Research Centerarch Center); Torben Bach Pedersen (Aalborg University)

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9:42 - 10:00am
Anna Mitsopoulou (Athena Research Centerarch and Innovation Center)*; Georgia Koutrika (Athena Research Centerarch Center)

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10:00 - 10:30am Coffee Break
10:30 - 12:00pm Session 6: "Data Quality"
Chair: Anastasios Gounaris
10:30 - 10:48am
Luca Zecchini (BIFOLD & TU Berlin); Vasilis Efthymiou (Harokopio University of Athens)*; Felix Naumann (Hasso Plattner Institute); Giovanni Simonini (University of Modena & Reggio Emilia)

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10:48 - 11:06am
Michail Zervas (University of Macedonia ); Alexandros Karakasidis (University of Macedonia)*

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11:06 - 11:24am
Christina Christodoulakis (University of Toronto)*; Moshe Gabel (University of Toronto); Angela Demke Brown (University of Toronto)

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11:24 - 11:42am
Nikolaos Myrtakis (University of Crete)*; Ioannis Tsamardinos (University of Crete); Vassilis Christophides (ENSEA)

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11:42 - 12:00pm Giorgos Alexiou (Athena Research Center)*; George Papastefanatos (Athena Research Center); Vassilis Stamatopoulos (Athena Research Center ); Georgia Koutrika (Athena Research Center ); Nectarios Koziris (National Technical University Athens)

Click to display the abstract Abstract: This work investigates the challenge of accurately and efficiently answering complex SPJ (Select-Project-Join) queries issued directly on top of dirty data. We introduce QueryER , a novel framework that seamlessly integrates Entity Resolution (ER) into traditional query processing. QueryER performs analysis-aware deduplication by incorporating ER operators into the query plan, enabling efficient entity resolution over dirty data containing duplicate entries with minimal pre-processing time and no manual preparation overhead. Our comprehensive experimental evaluation, conducted using both real-world and synthetic datasets, demonstrates that QueryER adapts to the workload, exhibits sub-linear scalability, and consistently achieves high recall performance, outperforming baseline approaches. The results attest to the robustness of QueryER and its suitability for data exploration and analysis workflows. This work opens up new possibilities for more efficient query processing over dirty data, particularly in the realm of data analysis and exploration

12:00pm - 1:00pm Keynote: Data Management Strategies for Space-Efficient Decoding and Planning
Prof. Panagiotis Karras (University of Copenhagen, Denmark)
Click to display the abstract Abstract: Several key computer science tasks are traditionally solved via dynamic programming and need to work within the constraints of low-memory devices. This talk presents two solutions that enhance space-efficiency in such tasks. First, we will show how to achieve space-efficient Viterbi decoding, used in speech recognition and probabilistic context-free grammar parsing. Second, we will outline how to make optimal planning decisions space-efficiently in a finite-horizon Markov Decision Process. Thereby, we will showcase how data management expertise can deliver solutions in other domains. Lastly, we will glimpse into alternative time-efficient strategies for those problems.

1:00 - 2:00pm Lunch Break
3:00 - 3:36pm Session 7: "Data Mining"
Chair: Panos Kalnis
3:00 - 3:18pm
Petri Puustinen (Tampere University); Maria Stratigi (Tampere University); Kostas Stefanidis (Tampere University)*

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3:18 - 3:36pm
Aryan Esmailpour (University of Illinois Chicago); Stavros Sintos (University of Illinois Chicago)*

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3:36 - 4:00pm Coffee Break
4:00 - 5:45pm Session 8: "Sponsored Talks"
Chair: Haralampos Gavriilidis
4:00 - 4:15pm Sponsored Talk: I Asked AI To Optimize My Database
Giannis Panselinas (Natech)
4:15 - 4:30pm Sponsored Talk: IT Disaster Recovery Program at COSMOTE TELEKOM
Fragkiskos Pentaris (Cosmote Telekom)
4:30 - 4:45pm Sponsored Talk: Kpler Research Labs
Georgios Grigoropoulos (Kpler)
4:45 - 5:45pm Panel: Will AI Kill Traditional Data Management?
Chair: Kostas Stefanidis
Herodotos Herodotou, Georgia Koutrika, Christos Tryfonopoulos
5:45 - 6:00pm HDMS Closing