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Documents authored by Hogan, Aidan


Document
Preface
Transactions on Graph Data and Knowledge

Authors: Aidan Hogan, Ian Horrocks, Andreas Hotho, and Lalana Kagal

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
Transactions on Graph Data and Knowledge (TGDK) is a new journal publishing peer-reviewed research on graph-based abstractions for data and knowledge, as well as the techniques, theories, applications and results that arise in this setting. TGDK is a community-run, Diamond Open Access journal, meaning that papers are published openly on the Web without fees for authors or readers. In this preface, we provide some brief remarks about the rationale and goals of the new journal, followed by an introduction to its inaugural issue, entitled "Trends in Graph Data and Knowledge", which collects together 12 diverse vision, position and survey papers on the types of research topics that exemplify the scope of this new journal.

Cite as

Aidan Hogan, Ian Horrocks, Andreas Hotho, and Lalana Kagal. Transactions on Graph Data and Knowledge. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 1:1-1:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@Article{hogan_et_al:TGDK.1.1.1,
  author =	{Hogan, Aidan and Horrocks, Ian and Hotho, Andreas and Kagal, Lalana},
  title =	{{Transactions on Graph Data and Knowledge}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:4},
  ISSN =	{2942-7517},
  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.1.1.1},
  URN =		{urn:nbn:de:0030-drops-194757},
  doi =		{10.4230/TGDK.1.1.1},
  annote =	{Keywords: Graphs, Data, Knowledge}
}
Document
Invited Paper
Knowledge Graphs: A Guided Tour (Invited Paper)

Authors: Aidan Hogan

Published in: OASIcs, Volume 99, International Research School in Artificial Intelligence in Bergen (AIB 2022)


Abstract
Much has been written about knowledge graphs in the past years by authors coming from diverse communities. The goal of these lecture notes is to provide a guided tour to the secondary and tertiary literature concerning knowledge graphs where the reader can learn more about particular topics. In particular, we collate together brief summaries of relevant books, book collections, book chapters, journal articles and other publications that provide introductions, primers, surveys and perspectives regarding: knowledge graphs in general; graph data models and query languages; semantics in the form of graph schemata, ontologies and rules; graph theory, algorithms and analytics; graph learning, in the form of knowledge graph embeddings and graph neural networks; and the knowledge graph life-cycle, which incorporates works on constructing, refining and publishing knowledge graphs. Where available, we highlight and provide direct links to open access literature.

Cite as

Aidan Hogan. Knowledge Graphs: A Guided Tour (Invited Paper). In International Research School in Artificial Intelligence in Bergen (AIB 2022). Open Access Series in Informatics (OASIcs), Volume 99, pp. 1:1-1:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{hogan:OASIcs.AIB.2022.1,
  author =	{Hogan, Aidan},
  title =	{{Knowledge Graphs: A Guided Tour}},
  booktitle =	{International Research School in Artificial Intelligence in Bergen (AIB 2022)},
  pages =	{1:1--1:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-228-0},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{99},
  editor =	{Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.AIB.2022.1},
  URN =		{urn:nbn:de:0030-drops-159999},
  doi =		{10.4230/OASIcs.AIB.2022.1},
  annote =	{Keywords: knowledge graphs}
}
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