=Paper=
{{Paper
|id=None
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-637/preface.pdf
|volume=Vol-637
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<pdf width="1500px">https://ceur-ws.org/Vol-637/preface.pdf</pdf>
<pre>
     Workshop on Semantic Data Management

     Reto Krummenacher, Atanas Kiryakov, Karl Aberer, and Rajaraman
                             Kanagasabai

                       Semantic Data Management Initiative
                                www.semdata.org

    The Semantic Web represents the next generation Web of Data, where data
is published and interlinked in order to facilitate the exploitation of its structure
and meaning. Semantic applications require database management systems for
the handling of structured data, taking into consideration the models used to rep-
resent semantics. To foster the realization of the Semantic Web, the World Wide
Web Consortium (W3C) developed a set of metadata models, ontology mod-
els, and query languages. Most of the Semantic Web repositories are database
engines, which store data represented in RDF, support SPARQL queries, and
can interpret ontologies represented in RDFS and OWL. We are at the point
where the adoption of semantic technologies is growing. However, these tech-
nologies often appear to be immature, and tend to be too expensive or risky
to deploy in real business. Solid data management concepts, architectures, and
tools are important for the semantic ecosystem, and creating them requires a
strong community, with a critical mass of involvement.
    Semantic data management refers to a range of techniques for the manipu-
lation and usage of data based on its meaning. It enables sustainable solutions
for a range of IT settings, where the usage of mainstream technology is ineffi-
cient or entirely unfeasible: enterprise data integration, life science research, data
sharing in SaaS architectures, querying linked data on the Web. In a nutshell,
semantic data management fosters the economy of knowledge, facilitating more
comprehensive usage of larger scale and more complex datasets at lower cost.
    The SemData workshop provided a platform for the investigation of various
aspects related to semantic databases and data management, such as seman-
tic repositories, their virtualization and distribution, and interoperability with
related database solutions. Many of the semantic data management challenges
cumulate in the need for scalable database solutions for semantic data, a build-
ing block that runs largely behind comparable non-semantic solutions. In order
to make semantic technologies take on the market, it is indispensable that tech-
nological progress allows semantic repositories to reach near performance parity
with some of the best RDBMS solutions without having to omit the advantages
of a higher query expressivity compared to basic key-value stores, or the higher
schema flexibility compared to the relational model. It is time that one must no
longer pay a heavy price in terms of longer run times or more expensive equip-
ment for profiting from the flexibility of the generic physical model underlying
the semantic graph-based structures of RDF. We recognize that there will always
be a burden with more flexibility, hence, the goal is to minimize the drawbacks
and maximize the advantages of the semantic repositories.

</pre>