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Documents authored by Bonifati, Angela

Document
Position
DOI: 10.4230/TGDK.1.1.2
Large Language Models and Knowledge Graphs: Opportunities and Challenges

Authors: Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, and Damien Graux

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Large Language Models (LLMs) have taken Knowledge Representation - and the world - by storm. This inflection point marks a shift from explicit knowledge representation to a renewed focus on the hybrid representation of both explicit knowledge and parametric knowledge. In this position paper, we will discuss some of the common debate points within the community on LLMs (parametric knowledge) and Knowledge Graphs (explicit knowledge) and speculate on opportunities and visions that the renewed focus brings, as well as related research topics and challenges.
Cite as

Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, and Damien Graux. Large Language Models and Knowledge Graphs: Opportunities and Challenges. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 2:1-2:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{pan_et_al:TGDK.1.1.2,
  author =	{Pan, Jeff Z. and Razniewski, Simon and Kalo, Jan-Christoph and Singhania, Sneha and Chen, Jiaoyan and Dietze, Stefan and Jabeen, Hajira and Omeliyanenko, Janna and Zhang, Wen and Lissandrini, Matteo and Biswas, Russa and de Melo, Gerard and Bonifati, Angela and Vakaj, Edlira and Dragoni, Mauro and Graux, Damien},
  title =	{{Large Language Models and Knowledge Graphs: Opportunities and Challenges}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:38},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.2},
  URN =		{urn:nbn:de:0030-drops-194766},
  doi =		{10.4230/TGDK.1.1.2},
  annote =	{Keywords: Large Language Models, Pre-trained Language Models, Knowledge Graphs, Ontology, Retrieval Augmented Language Models}
}
Document
Survey
DOI: 10.4230/TGDK.1.1.11
How Does Knowledge Evolve in Open Knowledge Graphs?

Authors: Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
Cite as

Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs. How Does Knowledge Evolve in Open Knowledge Graphs?. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 11:1-11:59, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{polleres_et_al:TGDK.1.1.11,
  author =	{Polleres, Axel and Pernisch, Romana and Bonifati, Angela and Dell'Aglio, Daniele and Dobriy, Daniil and Dumbrava, Stefania and Etcheverry, Lorena and Ferranti, Nicolas and Hose, Katja and Jim\'{e}nez-Ruiz, Ernesto and Lissandrini, Matteo and Scherp, Ansgar and Tommasini, Riccardo and Wachs, Johannes},
  title =	{{How Does Knowledge Evolve in Open Knowledge Graphs?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{11:1--11:59},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.11},
  URN =		{urn:nbn:de:0030-drops-194855},
  doi =		{10.4230/TGDK.1.1.11},
  annote =	{Keywords: KG evolution, temporal KG, versioned KG, dynamic KG}
}
Document
DOI: 10.4230/DagRep.9.12.1
Big Graph Processing Systems (Dagstuhl Seminar 19491)

Authors: Angela Bonifati, Alexandru Iosup, Sherif Sakr, and Hannes Voigt

Published in: Dagstuhl Reports, Volume 9, Issue 12 (2020)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19491 "Big Graph Processing Systems". We are just beginning to understand the role graph processing could play in our society. Data is not just getting bigger, but, crucially, also more connected. Exploring, describing, predicting, and explaining real- and digital-world phenomena is increasingly relying on abstractions that can express interconnectedness. Graphs are such an abstraction. They can model naturally the complex relationships, interactions, and interdependencies between objects. However, after initial success, graph processing systems are struggling to cope with the new scale, diversity, and other real-world needs. The Dagstuhl Seminar 19491 aims to addresses the question: How could the next decade look like for graph processing systems? To identify the opportunities and challenges of graph processing systems over the next decade, we met in December 2019 with circa 40 high-quality and diverse researchers for the Dagstuhl Seminar on Big Graph Processing Systems. A main strength of this seminar is the combination of the data management and large-scale systems communities. The seminar was successful, and addressed in particular topics around graph processing systems: ecosystems, abstractions and other fundamental theory, and performance.
Cite as

Angela Bonifati, Alexandru Iosup, Sherif Sakr, and Hannes Voigt. Big Graph Processing Systems (Dagstuhl Seminar 19491). In Dagstuhl Reports, Volume 9, Issue 12, pp. 1-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Article{bonifati_et_al:DagRep.9.12.1,
  author =	{Bonifati, Angela and Iosup, Alexandru and Sakr, Sherif and Voigt, Hannes},
  title =	{{Big Graph Processing Systems (Dagstuhl Seminar 19491)}},
  pages =	{1--27},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{12},
  editor =	{Bonifati, Angela and Iosup, Alexandru and Sakr, Sherif and Voigt, Hannes},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.12.1},
  URN =		{urn:nbn:de:0030-drops-120098},
  doi =		{10.4230/DagRep.9.12.1},
  annote =	{Keywords: Abstractions, Big Data, Big Graph, data management, Ecosystems, graph processing, Performance, systems, Theory}
}
Document
DOI: 10.4230/DagSemProc.08261.6
An In-Memory XQuery/XPath Engine over a Compressed Structured Text Representation

Authors: Angela Bonifati, Gregory Leighton, Veli Mäkinen, Sebastian Maneth, Gonzalo Navarro, and Andrea Pugliese

Published in: Dagstuhl Seminar Proceedings, Volume 8261, Structure-Based Compression of Complex Massive Data (2008)

Abstract
We describe the architecture and main algorithmic design decisions for an XQuery/XPath processing engine over XML collections which will be represented using a self-indexing approach, that is, a compressed representation that will allow for basic searching and navigational operations in compressed form. The goal is a structure that occupies little space and thus permits manipulating large collections in main memory.
Cite as

Angela Bonifati, Gregory Leighton, Veli Mäkinen, Sebastian Maneth, Gonzalo Navarro, and Andrea Pugliese. An In-Memory XQuery/XPath Engine over a Compressed Structured Text Representation. In Structure-Based Compression of Complex Massive Data. Dagstuhl Seminar Proceedings, Volume 8261, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{bonifati_et_al:DagSemProc.08261.6,
  author =	{Bonifati, Angela and Leighton, Gregory and M\"{a}kinen, Veli and Maneth, Sebastian and Navarro, Gonzalo and Pugliese, Andrea},
  title =	{{An In-Memory XQuery/XPath Engine over a Compressed Structured Text Representation}},
  booktitle =	{Structure-Based Compression of Complex Massive Data},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8261},
  editor =	{Stefan B\"{o}ttcher and Markus Lohrey and Sebastian Maneth and Wojcieh Rytter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08261.6},
  URN =		{urn:nbn:de:0030-drops-16776},
  doi =		{10.4230/DagSemProc.08261.6},
  annote =	{Keywords: Compressed self-index, compressed XML representation, XPath, XQuery}
}
Document
DOI: 10.4230/DagSemProc.08261.9
Optimizing XML Compression in XQueC

Authors: Andrei Arion, Angela Bonifati, Ioana Manolescu, and Andrea Pugliese

Published in: Dagstuhl Seminar Proceedings, Volume 8261, Structure-Based Compression of Complex Massive Data (2008)

Abstract
We present our approach to the problem of optimizing compression choices in the context of the XQueC compressed XML database system. In XQueC, data items are aggregated into containers, which are further grouped to be compressed together. This way, XQueC is able to exploit data commonalities and to perform query evaluation in the compressed domain, with the aim of improving both compression and querying performance. However, different compression algorithms have different performance and support different sets of operations in the compressed domain. Therefore, choosing how to group containers and which compression algorithm to apply to each group is a challenging issue. We address this problem through an appropriate cost model and a suitable blend of heuristics which, based on a given query workload, are capable of driving appropriate compression choices.
Cite as

Andrei Arion, Angela Bonifati, Ioana Manolescu, and Andrea Pugliese. Optimizing XML Compression in XQueC. In Structure-Based Compression of Complex Massive Data. Dagstuhl Seminar Proceedings, Volume 8261, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{arion_et_al:DagSemProc.08261.9,
  author =	{Arion, Andrei and Bonifati, Angela and Manolescu, Ioana and Pugliese, Andrea},
  title =	{{Optimizing XML Compression in XQueC}},
  booktitle =	{Structure-Based Compression of Complex Massive Data},
  pages =	{1--12},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8261},
  editor =	{Stefan B\"{o}ttcher and Markus Lohrey and Sebastian Maneth and Wojcieh Rytter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08261.9},
  URN =		{urn:nbn:de:0030-drops-16924},
  doi =		{10.4230/DagSemProc.08261.9},
  annote =	{Keywords: XML compression}
}
Document
DOI: 10.4230/DagSemProc.08261.12
The XQueC Project: Compressing and Querying XML

Authors: Andrei Arion, Angela Bonifati, Ioana Manolescu, and Andrea Pugliese

Published in: Dagstuhl Seminar Proceedings, Volume 8261, Structure-Based Compression of Complex Massive Data (2008)

Abstract
We outline in this paper the main contributions of the XQueC project. XQueC, namely XQuery processor and Compressor, is the first compression tool to seamlessly allow XQuery queries in the compressed domain. It includes a set of data structures, that basically shred the XML document into suitable chunks linked to each other, thus disagreeing with the ’homomorphic’ principle so far adopted in previous XML compressors. According to this principle, the compressed document is homomorphic to the original document. Moreover, in order to avoid the time consumption due to compressing and decompressing intermediate query results, XQueC applies ‘lazy’ decompression by issuing the queries directly in the compressed domain.
Cite as

Andrei Arion, Angela Bonifati, Ioana Manolescu, and Andrea Pugliese. The XQueC Project: Compressing and Querying XML. In Structure-Based Compression of Complex Massive Data. Dagstuhl Seminar Proceedings, Volume 8261, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{arion_et_al:DagSemProc.08261.12,
  author =	{Arion, Andrei and Bonifati, Angela and Manolescu, Ioana and Pugliese, Andrea},
  title =	{{The XQueC Project: Compressing and Querying XML}},
  booktitle =	{Structure-Based Compression of Complex Massive Data},
  pages =	{1--16},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8261},
  editor =	{Stefan B\"{o}ttcher and Markus Lohrey and Sebastian Maneth and Wojcieh Rytter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08261.12},
  URN =		{urn:nbn:de:0030-drops-16919},
  doi =		{10.4230/DagSemProc.08261.12},
  annote =	{Keywords: XML compression, Data structures, XQuery querying}
}
Document
DOI: 10.4230/DagSemProc.06431.3
06431 Working Group Report on Managing and Integrating Data in P2P Databases

Authors: Peter A. Boncz, Angela Bonifati, Arantza Illarramendi, Peter Janacik, Birgitta König-Ries, Wolfgang Lehner, Pedro Jose Marrón, Wolfgang May, Aris Ouksel, Kay Römer, Brahmananda Sapkota, Kai-Uwe Sattler, Heinz Schweppe, Rita Steinmetz, and Can Türker

Published in: Dagstuhl Seminar Proceedings, Volume 6431, Scalable Data Management in Evolving Networks (2007)

Abstract
In this report, to our best recollection, we provide a summary of the working group "Managing and Integrating Data in P2P Databases" of the Dagstuhl Seminar nr. 6431 on "Scalable Data Management in Evolving Neworks", held on October 23-27 in Dagstuhl (Germany).
Cite as

Peter A. Boncz, Angela Bonifati, Arantza Illarramendi, Peter Janacik, Birgitta König-Ries, Wolfgang Lehner, Pedro Jose Marrón, Wolfgang May, Aris Ouksel, Kay Römer, Brahmananda Sapkota, Kai-Uwe Sattler, Heinz Schweppe, Rita Steinmetz, and Can Türker. 06431 Working Group Report on Managing and Integrating Data in P2P Databases. In Scalable Data Management in Evolving Networks. Dagstuhl Seminar Proceedings, Volume 6431, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{boncz_et_al:DagSemProc.06431.3,
  author =	{Boncz, Peter A. and Bonifati, Angela and Illarramendi, Arantza and Janacik, Peter and K\"{o}nig-Ries, Birgitta and Lehner, Wolfgang and Marr\'{o}n, Pedro Jose and May, Wolfgang and Ouksel, Aris and R\"{o}mer, Kay and Sapkota, Brahmananda and Sattler, Kai-Uwe and Schweppe, Heinz and Steinmetz, Rita and T\"{u}rker, Can},
  title =	{{06431 Working Group Report on Managing and Integrating Data in P2P Databases}},
  booktitle =	{Scalable Data Management in Evolving Networks},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6431},
  editor =	{Stefan B\"{o}ttcher and Le Gruenwald and Pedro Jose Marr\'{o}n and Evaggelia Pitoura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06431.3},
  URN =		{urn:nbn:de:0030-drops-9505},
  doi =		{10.4230/DagSemProc.06431.3},
  annote =	{Keywords: P2P database, data integration}
}
Document
DOI: 10.4230/DagSemProc.06431.5
06431 Working Group Summary: P2P, Ad Hoc and Sensor Networks – All the Different or All the Same?

Authors: Peter A. Boncz, Angela Bonifati, Joos-Hendrik Böse, Stefan Böttcher, Panos Kypros Chrysanthis, Le Gruenwald, Arantza Illarramendi, Peter Janacik, Birgitta König-Ries, Wolfgang May, Anirban Mondal, Sebastian Obermeier, Aris Ouksel, and George Samaras

Published in: Dagstuhl Seminar Proceedings, Volume 6431, Scalable Data Management in Evolving Networks (2007)

Abstract
Currently, data management technologies are in the process of finding their way into evolving networks, i.e. P2P, ad hoc and wireless sensor networks. We examine the properties, differences and commonalities of the different types of evolving networks, in order to enable the development of adequate technologies suiting their characteristics. We start with presenting definitions for the different network types, before arranging them in a network hierarchy, to gain a clear view of the area. Then, we analyze and compare the example applications for each of the types using different design dimensions. Based on this work, we finally present a comparison of P2P, ad hoc and wireless sensor networks.
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Peter A. Boncz, Angela Bonifati, Joos-Hendrik Böse, Stefan Böttcher, Panos Kypros Chrysanthis, Le Gruenwald, Arantza Illarramendi, Peter Janacik, Birgitta König-Ries, Wolfgang May, Anirban Mondal, Sebastian Obermeier, Aris Ouksel, and George Samaras. 06431 Working Group Summary: P2P, Ad Hoc and Sensor Networks – All the Different or All the Same?. In Scalable Data Management in Evolving Networks. Dagstuhl Seminar Proceedings, Volume 6431, pp. 1-7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{boncz_et_al:DagSemProc.06431.5,
  author =	{Boncz, Peter A. and Bonifati, Angela and B\"{o}se, Joos-Hendrik and B\"{o}ttcher, Stefan and Chrysanthis, Panos Kypros and Gruenwald, Le and Illarramendi, Arantza and Janacik, Peter and K\"{o}nig-Ries, Birgitta and May, Wolfgang and Mondal, Anirban and Obermeier, Sebastian and Ouksel, Aris and Samaras, George},
  title =	{{06431 Working Group Summary: P2P, Ad Hoc and Sensor Networks – All the Different or All the Same?}},
  booktitle =	{Scalable Data Management in Evolving Networks},
  pages =	{1--7},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6431},
  editor =	{Stefan B\"{o}ttcher and Le Gruenwald and Pedro Jose Marr\'{o}n and Evaggelia Pitoura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06431.5},
  URN =		{urn:nbn:de:0030-drops-9514},
  doi =		{10.4230/DagSemProc.06431.5},
  annote =	{Keywords: P2P, ad hoc, wireless sensor networks, database systems}
}
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