@article{horrocks2003making,
  abstract = {The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic Web. In this paper, we discuss how the philosophy and features of OWL can be traced back to these older formalisms, with modifications driven by several other constraints on OWL. Several interesting problems have arisen where these influences on OWL have clashed.},
  author = {Horrocks, Ian and Patel-Schneider, Peter F. and van Harmelen, Frank},
  doi = {10.1016/j.websem.2003.07.001},
  interhash = {2db7912282384be060b75ebb445dd5d1},
  intrahash = {6944f3b978dec082ffa284fe6bf7ac1a},
  issn = {1570-8268},
  journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
  number = 1,
  pages = {7-26},
  title = {From SHIQ and RDF to OWL: the making of a Web Ontology Language},
  url = {http://www.sciencedirect.com/science/article/pii/S1570826803000027},
  volume = 1,
  year = 2003
}

@article{goodwin2008geographical,
  abstract = {Ordnance Survey, the national mapping agency of Great Britain, is investigating how semantic web technologies assist its role as a geographical information provider. A major part of this work involves the development of prototype products and datasets in RDF. This article discusses the production of an example dataset for the administrative geography of Great Britain, demonstrating the advantages of explicitly encoding topological relations between geographic entities over traditional spatial queries. We also outline how these data can be linked to other datasets on the web of linked data and some of the challenges that this raises.},
  author = {Goodwin, John and Dolbear, Catherine and Hart, Glen},
  doi = {10.1111/j.1467-9671.2008.01133.x},
  interhash = {ea248d549690eceb8e7aa06ccb24e226},
  intrahash = {08412bb4afca1e86d0cca0a8a083f2a2},
  issn = {1467-9671},
  journal = {Transactions in GIS},
  pages = {19--30},
  publisher = {Blackwell Publishing Ltd},
  title = {Geographical Linked Data: The Administrative Geography of Great Britain on the Semantic Web},
  url = {http://dx.doi.org/10.1111/j.1467-9671.2008.01133.x},
  volume = 12,
  year = 2008
}

@inproceedings{daquin2011extracting,
  abstract = {With the rise of linked data, more and more semantically described information is being published online according to the principles and technologies of the Semantic Web (especially, RDF and SPARQL). The use of such standard technologies means that this data should be exploitable, integrable and reusable straight away. However, once a potentially interesting dataset has been discovered, significant efforts are currently required in order to understand its schema, its content, the way to query it and what it can answer. In this paper, we propose a method and a tool to automatically discover questions that can be answered by an RDF dataset. We use formal concept analysis to build a hierarchy of meaningful sets of entities from a dataset. These sets of entities represent answers, which common characteristics represent the clauses of the corresponding questions. This hierarchy can then be used as a querying interface, proposing questions of varying levels of granularity and specificity to the user. A major issue is however that thousands of questions can be included in this hierarchy. Based on an empirical analysis and using metrics inspired both from formal concept analysis and from ontology summarization, we devise an approach for identifying relevant questions to act as a starting point to the navigation in the question hierarchy.},
  acmid = {1999698},
  address = {New York, NY, USA},
  author = {d'Aquin, Mathieu and Motta, Enrico},
  booktitle = {Proceedings of the sixth international conference on Knowledge capture},
  doi = {10.1145/1999676.1999698},
  interhash = {7794150f2b42c21956eb7fb419ca0248},
  intrahash = {45374b975834248c0cd87022fc854e25},
  isbn = {978-1-4503-0396-5},
  location = {Banff, Alberta, Canada},
  numpages = {8},
  pages = {121--128},
  publisher = {ACM},
  title = {Extracting relevant questions to an RDF dataset using formal concept analysis},
  url = {http://doi.acm.org/10.1145/1999676.1999698},
  year = 2011
}

@article{shadbolt06semantic,
  abstract = {The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information—information derived from data through a semantic theory for interpreting the symbols. This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks; they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the Semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years. Furthermore, we see the use of ontologies in the e-science community presaging ultimate success for the Semantic Web—just as the use of HTTP within the CERN particle physics community led to the revolutionary success of the original Web.},
  author = {Shadbolt, Nigel and Berners-Lee, Tim and Hall, Wendy},
  editor = {Staab, Steffen},
  ee = {http://dsonline.computer.org/portal/site/dsonline/menuitem.9ed3d9924aeb0dcd82ccc6716bbe36ec/index.jsp?&pName=dso_level1&path=dsonline/2006/07&file=x3sem.xml&xsl=article.xsl&},
  interhash = {5f95e416982e7d981e2d6daa988180bc},
  intrahash = {ae5cd5e31f0d7847f323a59988fdfab8},
  journal = {IEEE Intelligent Systems},
  number = 3,
  pages = {96-101},
  title = {The Semantic Web Revisited},
  url = {http://eprints.ecs.soton.ac.uk/12614/01/Semantic_Web_Revisted.pdf#search=%22The%20Semantic%20Web%20Revisited%22},
  volume = 21,
  year = 2006
}