The seminar is devoted to the theory and practice of data management and knowledge representation. We are interested in challenges related to the processing of data, queries, and metadata (schemas, constraints, dependencies, ontologies), ranging from designing and analyzing abstract formalisms all the way to database systems architecture and distributed processing of big data. We like our data in all flavors: not only relational, but also semistructured (XML, JSON), graph (RDF, LPG), object, text, temporal, stream, GIS, and others.
The problems tackled can be theoretical, requiring tools from algorithmics, combinatorics, logic (e.g. finite model theory), and automata theory, as well as very practical, in the spirit of systems and software engineering. MSc theses written within our seminar may study decidability and complexity of abstract problems, design algorithms and heuristics, implement and experiment with existing theoretical solutions, or analyze, compare and extend existing systems.
We meet and discuss with experts in other disciplines, who sometimes supply ideas for MSc theses. We have cooperated or are currently cooperating with astronomers, chemists, and geographers. We are also open for other areas where databases can be applied.
Seminar presentations are usually based on recent papers presented at leading international conferences devoted to data management and knowledge representation, such as VLDB, PODS, SIGMOD, or KR.
Selected topics:
* Data models, semantics, query languages
* Data provenance
* Databases for emerging hardware
* Distributed and parallel databases
* Graph data management, RDF, social networks, Semantic Web
* Knowledge discovery, clustering, data mining
* Machine learning for data management and vice versa
* Model theory, logics, algebras, computational complexity
* Ontology-based data access, data integration and exchange, metadata management
* Ontology formalisms and models, description logics
* Privacy, security, ethics
* Query processing and optimization
* Scientific databases
* Semi-structured data
* Small data, end-user programming
* Storage, indexing, and physical database design
* Streams, sensor networks, complex event processing
* Transaction processing
* Uncertainty, incompleteness, and inconsistency in data management
Organizers
- dr hab. Filip Murlak, prof. ucz.
- dr Jacek Sroka
- prof. dr hab. Krzysztof Stencel
- prof. dr hab. Jerzy Tyszkiewicz
Information
Tuesdays, 10:15 a.m. , room: 4060Home page
https://sites.google.com/view/sembdmimuw?pli=1&authuser=1Research fields
List of talks
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Oct. 15, 2024, 11 a.m.
Krzysztof Stencel (MIMUW)
Jak przestałem się martwić i pokochałem ChatGPT (How I Learned to Stop Worrying and Love ChatGPT)
In the dynamic landscape of software engineering, the emergence of ChatGPT-generated code signifies a distinctive and evolving paradigm in development practices. We delve into the impact of interactions with ChatGPT on the software development process, …
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Oct. 15, 2024, 10:15 a.m.
Michał Jadwiszczak (MIMUW)
Rozproszone agregaty w rozproszonej szerokokolumnowej bazie danych (Distributed aggregation in a distributed wide-column database)
Distributed databases in comparison to single-server databases open a wide area of new possibilities. While there is a potential of increasing the throughput, reducing the execution time and making more efficient use of machines, there …
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June 6, 2024, 12:15 p.m.
Grzegorz Bogusław Zaleski (MIMUW)
A comparison of software measures with a subjective assessment of quality (Porównanie miar oprogramowania z subiektywną oceną jakości)
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May 23, 2024, 12:15 p.m.
Jacek Ciszewski (MIMUW)
PG schema validation
Recent years have seen property graph databases popularity and demand rising. With great focus in the field put on graph query languages, a variety of existing graph schemas differs substantially in supported features, with upcoming …
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April 25, 2024, 12:15 p.m.
Marcin Mordecki (MIMUW)
Stackless Processing of Streamed Trees - cont. (Stackless Processing of Streamed Trees - kont.)
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April 4, 2024, 12:15 p.m.
Łukasz Orawiec (MIMUW)
QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting
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March 21, 2024, 12:15 p.m.
Piotr Ulanowski (MIMUW)
Parsing Gigabytes of JSON per Second (Wektoryzacja do parsowania gigabajtów danych plików JSON w ciągu sekund)
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March 14, 2024, 12:15 p.m.
Alexandra Rogova (IRIF, Université de Paris, Francja.)
Property Graph Languages
The development of practical query languages for graph databases runs well ahead of the underlying theory. The ISO committee in charge of database query languages is currently developing a new standard called Graph Query Language …
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Feb. 29, 2024, 12:15 p.m.
Jakub Pawlewicz (MIMUW)
Indeksy wyuczone na danych; najnowsze wyniki
Mając dany niemalejący ciąg liczb S = {x_1, ..., x_n}, chcemy odpowiadać na pytania, gdzie wpadłby nowy klucz k: |{x \in S | x < k}|. Zakładamy, że S jest ustalone raz, a my chcemy …
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Jan. 25, 2024, 12:15 p.m.
Michał J. Gajda (MigaMake Pte Ltd)
Towards a perfect union type: automatic typing of JSON documents
We present a principled theoretical framework for inferring and checking the union types, and show its work in practice on JSON data structures. The framework poses a union type inference as a learning problem from …
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Jan. 18, 2024, 12:15 p.m.
Kacper Konecki: (MIMUW)
Immersyjna wizualizacja systemu kontroli wersji
Referat będzie o przeprowadzonej próbie wizualizacji zmian w repozytoriach kodu przy użyciu środowisk rzeczywistości wirtualnej (VR) oraz rozszerzonej rzeczywistości (AR). Na wstępie przedstawię prototyp stworzonego narzędzia, które umożliwia wizualizację historii modyfikacji w repozytoriach Git. Następnie …
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Jan. 11, 2024, 12:15 p.m.
Piotr Ulanowski (MIMUW)
ByteStore: Hybrid Layouts for Main-Memory Column Stores
Bazy Kolumnowe są obecnie używane do przeprowadzania analiz na dużych danych relacyjnych. Takie analizy zazwyczaj składają się z read-only zapytań. Po wykonaniu tych zapytań, dane są następnie przekazywane do dalszej analizy takiej jak agregacja czy …
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Dec. 21, 2023, 12:15 p.m.
Łukasz Orawiec (MIMUW)
InfiniStore: Elastic Serverless Cloud Storage
Model Function-as-a-Service pozwala tworzyć systemy, będące zbiorami funkcji umożliwiających wykonywanie kodu bez konieczności zarządzania infrastrukturą. Natychmiastowe i automatyczne skalowanie funkcji, zapewniane przez usługodawcę, szybki dostęp do danych przechowywanych w instancjach funkcji oraz korzystne naliczanie opłat …