Search Results

Documents authored by Scherp, Ansgar


Document
Survey
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)


Copy BibTex To Clipboard

@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
Survey
Structural Summarization of Semantic Graphs Using Quotients

Authors: Ansgar Scherp, David Richerby, Till Blume, Michael Cochez, and Jannik Rau

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
Graph summarization is the process of computing a compact version of an input graph while preserving chosen features of its structure. We consider semantic graphs where the features include edge labels and label sets associated with a vertex. Graph summaries are typically much smaller than the original graph. Applications that depend on the preserved features can perform their tasks on the summary, but much faster or with less memory overhead, while producing the same outcome as if they were applied on the original graph. In this survey, we focus on structural summaries based on quotients that organize vertices in equivalence classes of shared features. Structural summaries are particularly popular for semantic graphs and have the advantage of defining a precise graph-based output. We consider approaches and algorithms for both static and temporal graphs. A common example of quotient-based structural summaries is bisimulation, and we discuss this in detail. While there exist other surveys on graph summarization, to the best of our knowledge, we are the first to bring in a focused discussion on quotients, bisimulation, and their relation. Furthermore, structural summarization naturally connects well with formal logic due to the discrete structures considered. We complete the survey with a brief description of approaches beyond structural summaries.

Cite as

Ansgar Scherp, David Richerby, Till Blume, Michael Cochez, and Jannik Rau. Structural Summarization of Semantic Graphs Using Quotients. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 12:1-12:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


Copy BibTex To Clipboard

@Article{scherp_et_al:TGDK.1.1.12,
  author =	{Scherp, Ansgar and Richerby, David and Blume, Till and Cochez, Michael and Rau, Jannik},
  title =	{{Structural Summarization of Semantic Graphs Using Quotients}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{12:1--12:25},
  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.1.1.12},
  URN =		{urn:nbn:de:0030-drops-194862},
  doi =		{10.4230/TGDK.1.1.12},
  annote =	{Keywords: graph summarization, quotients, stratified bisimulation}
}
Document
Linking the Semantics Ecosystem with Semantics Derivation Rules for Multimedia Content

Authors: Ansgar Scherp

Published in: Dagstuhl Seminar Proceedings, Volume 8251, Contextual and Social Media Understanding and Usage (2009)


Abstract
Multimedia content exhibits multiple semantics that is influenced by different factors like time, contextual use, and personal background. With the semantics ecosystem, we find an elegant and high-level description of the different factors that influence the semantics of multimedia content. On the other hand, semantics derivation rules are a concrete means to extract and to derive semantics of multimedia content while authoring it. These rules are directly applicable in concrete applications and domains. Thus, there is a gap between the high-level ecosystem and the concrete semantics derivation rules. In this position paper, we propose the use of an ontology-based description of events to combine the high-level description of the semantics ecosystem with the concrete method of semantics derivation for page-based multimedia presentations.

Cite as

Ansgar Scherp. Linking the Semantics Ecosystem with Semantics Derivation Rules for Multimedia Content. In Contextual and Social Media Understanding and Usage. Dagstuhl Seminar Proceedings, Volume 8251, pp. 1-3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2009)


Copy BibTex To Clipboard

@InProceedings{scherp:DagSemProc.08251.6,
  author =	{Scherp, Ansgar},
  title =	{{Linking the Semantics Ecosystem with Semantics Derivation Rules for Multimedia Content}},
  booktitle =	{Contextual and Social Media Understanding and Usage},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8251},
  editor =	{Susanne Boll and Mohan S. Kankanhalli and Gopal Pingali and Svetha Venkatesh},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08251.6},
  URN =		{urn:nbn:de:0030-drops-20219},
  doi =		{10.4230/DagSemProc.08251.6},
  annote =	{Keywords: Multimedia Semantics, Semantics Ecosystem, Semantics Derivation, Event Ontology}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail