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Preface

Data Management for (Knowledge) Graphs

Authors: Stefania Dumbrava, George Fletcher, Matteo Lissandrini, and Riccardo Tommasini

Published in: TGDK, Volume 4, Issue 2 (2024): Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge, Volume 4, Issue 2

Abstract

In this Special Issue of Transactions on Graph Data and Knowledge, entitled "Data Management for (Knowledge) Graphs", we present eight articles: one position paper, four research papers, and three resource papers. These span graph data querying, transformation, integration, evolution, and evaluation. Their applications include legislative knowledge management, geospatial data access, and knowledge graph construction from heterogeneous sources with large language models.

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Stefania Dumbrava, George Fletcher, Matteo Lissandrini, and Riccardo Tommasini. Data Management for (Knowledge) Graphs. In Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 2, pp. 1:1-1:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{dumbrava_et_al:TGDK.4.2.1,
  author =	{Dumbrava, Stefania and Fletcher, George and Lissandrini, Matteo and Tommasini, Riccardo},
  title =	{{Data Management for (Knowledge) Graphs}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:2},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.2.1},
  URN =		{urn:nbn:de:0030-drops-275828},
  doi =		{10.4230/TGDK.4.2.1},
  annote =	{Keywords: graph data, property graphs, knowledge graphs, RDF, data management}
}

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Position

DOI: 10.4230/TGDK.4.2.2

How Human-Centric Are Our Graph Data Abstractions?

Authors: Angela Bonifati, Anastasia Dimou, Stefania Dumbrava, George Fletcher, Katja Hose, George Konstantinidis, Jose Emilio Labra Gayo, Wim Martens, Nina Pardal, Liat Peterfreund, Katherine Thornton, Maria-Esther Vidal, and Hannes Voigt

Published in: TGDK, Volume 4, Issue 2 (2024): Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge, Volume 4, Issue 2

Abstract

Graph data abstractions are often assumed to be intuitive, but experience shows that they are not equally understandable or usable in practice. In this vision and challenges paper, we examine the human-centricity of contemporary graph data abstractions through four lenses: researchability, usability, teachability, and societal impact. Drawing on diverse real-world use cases, ranging from clinical data and collaborative knowledge bases to biological and pangenomic graphs, we distill insights from database research, human-computer interaction, and education. Based on this analysis, we identify open research challenges that must be addressed to make graph abstractions easier to study, use, learn, and reason about.

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Angela Bonifati, Anastasia Dimou, Stefania Dumbrava, George Fletcher, Katja Hose, George Konstantinidis, Jose Emilio Labra Gayo, Wim Martens, Nina Pardal, Liat Peterfreund, Katherine Thornton, Maria-Esther Vidal, and Hannes Voigt. How Human-Centric Are Our Graph Data Abstractions?. In Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 2, pp. 2:1-2:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{bonifati_et_al:TGDK.4.2.2,
  author =	{Bonifati, Angela and Dimou, Anastasia and Dumbrava, Stefania and Fletcher, George and Hose, Katja and Konstantinidis, George and Gayo, Jose Emilio Labra and Martens, Wim and Pardal, Nina and Peterfreund, Liat and Thornton, Katherine and Vidal, Maria-Esther and Voigt, Hannes},
  title =	{{How Human-Centric Are Our Graph Data Abstractions?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:31},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.2.2},
  URN =		{urn:nbn:de:0030-drops-275837},
  doi =		{10.4230/TGDK.4.2.2},
  annote =	{Keywords: graph data abstractions, property graphs, RDF, human-centric data management, usability, computing education}
}

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Data Management for (Knowledge) Graphs

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How Human-Centric Are Our Graph Data Abstractions?

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