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    <journal-meta>
      <journal-title-group>
        <journal-title>Hersonissos, Greece
caebel@cs.aau.dk (C. Aebeloe); amr.azzam@wu.ac.at (A. Azzam); olaf.hartig@liu.se (O. Hartig);
khose@cs.aau.dk (K. Hose)</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>1st International Workshop on Data Management for Knowledge Graphs (DMKG 2023)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Christian Aebeloe</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Amr Azzam</string-name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Olaf Hartig</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Katja Hose</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of Computer Science, Aalborg University</institution>
          ,
          <country country="DK">Denmark</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Department of Computer and Information Science (IDA), Linköping University</institution>
          ,
          <country country="SE">Sweden</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Department of Informatics, Vienna University of Technology</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Department of Informations Systems and Operations, Vienna University of Economics and Business</institution>
          ,
          <country country="AT">Austria</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2023</year>
      </pub-date>
      <volume>000</volume>
      <fpage>0</fpage>
      <lpage>0003</lpage>
      <abstract>
        <p>The rapid increase in the adoption of knowledge graphs over the past years, both in the open data domain as well as in industry, means that data management solutions for knowledge graphs today have to support ever increasing amounts of data. In the face of the challenges arising from this problem, such as storing and indexing of knowledge graphs at scale, DMKG 2023 was inviting junior as well as more experienced researchers to discuss their initial ideas and approaches, which may not yet be extensive enough for full conference papers within the areas of Data Management for Knowledge Graphs.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Data management</kwd>
        <kwd>knowledge graphs</kwd>
        <kwd>Semantic Web</kwd>
        <kwd>Linked Data</kwd>
        <kwd>storage and management</kwd>
        <kwd>analytics and exploration</kwd>
        <kwd>querying and benchmarking</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Preface</title>
      <p>The DMKG 2023 workshop (https://dmkg-workshop.github.io/) provided an open forum for
early-stage as well as established researchers, software engineers, industry partners, and domain
experts to present and discuss emerging ideas and solutions within the area of Data Management
for Knowledge Graphs. Such ideas and approaches include research work that is not yet extensive
enough for a full conference publication, but which still facilitates valuable discussions within
the community.</p>
      <p>The DMKG workshop invited novel research and advances in scalable data management
solutions for large-scale knowledge graphs. Such data management solutions include techniques
for storage and indexing, partitioning for decentralized/centralized systems, archiving and
versioning, validation with SHACL/shEx, or federated data management.</p>
      <p>The DMKG 2023 workshop was co-located with the 20th Extended Semantic Web Conference
(ESWC 2023) in Hersonissos, Greece, on May 29th, 2023. The co-location of the workshop with
ESWC 2023 allowed for facilitating the workshop for a wide audience of knowledge graph
experts, data scientists, industry partners, and other interested parties. In total, at least 38
participants attended the workshop throughout its duration.</p>
      <p>We received a total of 7 submissions for the workshop, 5 of which were accepted for publication
and included in the proceedings. Of the 5 accepted papers, 1 was a short paper, 1 was a vision
paper, and the remaining 3 papers were regular research papers.</p>
    </sec>
    <sec id="sec-2">
      <title>2. Keynote</title>
      <p>The program for DMKG 2023 included a keynote by Andreas Harth (Professor of Technical
Information Systems at Friedrich-Alexander-Universität Erlangen-Nürnberg) entitled "Data
Management in Planet-Scale Hyperlinked Environments". In his keynote, Andreas considered the
decentralized infrastructure of the Web and important future use cases that this infrastructure is
crucial to address. He surveyed recent Web standards that facilitate accessing and manipulating
graph-structured representations of the physical world, such as Linked Data, Social Linked Data
(Solid), and the Web of Things. Then, he presented systems and applications that operate over
interfaces that adhere to these standards. Last, Andreas concluded his talk with an outlook to
future developments within decentralized data management for knowledge graphs.
3. Program Committee</p>
    </sec>
    <sec id="sec-3">
      <title>Acknowledgements</title>
      <p>We would like to thank all contributors, the program committee, the keynote speaker, and the
authors for their contributions. Furthermore, we wish to thank the attendees of the workshop
for making the DMKG a great venue to discuss preliminary work in data management for
knowledge graphs.</p>
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