In this introductory chapter we give a brief overview on the Linked Data concept, the Linked Data lifecycle as well as the LOD2 Stack – an integrated distribution of aligned tools which support the whole life cycle of Linked Data from extraction, authoring/creation via enrichment, interlinking, fusing to maintenance. The stack is designed to be versatile; for all functionality we define clear interfaces, which enable the plugging in of alternative third-party implementations. The architecture of the LOD2 Stack is based on three pillars: (1) Software integration and deployment using the Debian packaging system. (2) Use of a central SPARQL endpoint and standardized vocabularies for knowledge base access and integration between the different tools of the LOD2 Stack. (3) Integration of the LOD2 Stack user interfaces based on REST enabled Web Applications. These three pillars comprise the methodological and technological framework for integrating the very heterogeneous LOD2 Stack components into a consistent framework. The Semantic Web activity has gained momentum with the widespread publishing of structured data as RDF. The Linked Data paradigm has therefore evolved from a practical research idea into a very promising candidate for addressing one of the biggest challenges in the area of intelligent information management: the exploitation of the Web as a platform for data and information integration as well as for search and querying. Just as we publish unstructured textual information on the Web as HTML pages and search such information by using keyword-based search engines, we are already able to easily publish structured information, reliably interlink this information with other data published on the Web and search the resulting data space by using more expressive querying beyond simple keyword searches. The Linked Data paradigm has evolved as a powerful enabler for the transition of the current document-oriented Web into a Web of interlinked Data and, ultimately, into the Semantic Web. The term Linked Data here refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the past three years, leading to the creation of a global data space that contains many billions of assertions – the Web of Linked Data (cf. Fig. 1). In that context LOD2 targets a number of research challenges: improve coherence and quality of data published on the Web, close the performance gap between relational and RDF data management, establish trust on the Linked c © The Author(s) S. Auer et al. (Eds.): Linked Open Data, LNCS 8661, pp. 1–17, 2014. DOI: 10.1007/978-3-319-09846-3 1
[1]
Christian Bizer,et al.
The R2R Framework: Publishing and Discovering Mappings on the Web
,
2010,
COLD.
[2]
Previous version:
,
2004
.
[3]
Felix Naumann,et al.
Declarative Data Fusion - Syntax, Semantics, and Implementation
,
2005,
ADBIS.
[4]
Philipp Frischmuth,et al.
Weaving a Social Data Web with Semantic Pingback
,
2010,
EKAW.
[5]
Jeremy J. Carroll,et al.
Resource description framework (rdf) concepts and abstract syntax
,
2003
.
[6]
Maribel Acosta,et al.
Crowdsourcing Linked Data Quality Assessment
,
2013,
SEMWEB.
[7]
C. Bizer,et al.
Integrating product data from websites offering microdata markup
,
2014,
WWW.
[8]
Christian Bizer,et al.
Sieve: linked data quality assessment and fusion
,
2012,
EDBT-ICDT '12.
[9]
Tom Heath,et al.
Linked Data: Evolving the Web into a Global Data Space
,
2011,
Linked Data.
[10]
Robert Isele,et al.
Learning Expressive Linkage Rules using Genetic Programming
,
2012,
Proc. VLDB Endow..
[11]
Robert Isele,et al.
Silk Server - Adding missing Links while consuming Linked Data
,
2010,
COLD.
[12]
Robert Isele,et al.
Active learning of expressive linkage rules using genetic programming
,
2013,
J. Web Semant..
[13]
Christian Bizer,et al.
Learning conflict resolution strategies for cross-language Wikipedia data fusion
,
2014,
WWW '14 Companion.
[14]
Felix Naumann,et al.
Data fusion
,
2009,
CSUR.