http://www.ronpub.com/index.php/journals/OJSW/issues?volume=2&issue=1 All papers of this issue en-us https://www.ronpub.com/ojsw/OJSW_2015v2i1n01e_Groppe.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194864 The Web is everywhere in daily life. Business is not possible any more without the fast communication through the web. The knowledge of the humans is reflected in the information accessible in the web. New challenges occur with the flood of information and electronic possibilities for the human being. The current World Wide Web enables an easy, instant access to a vast amount of online information. However, the content in the Web is typically for human consumption, and is not tailored to be machine-processed. The Semantic Web, which is intended to establish a machine-understandable web, thereby offers a promising and potential solution to mining and analyzing web content. The Semantic Web is currently changing from an emergent trend to a technology used in complex real-world applications. This part of the special issue "Semantic and Web" especially investigates how semantic technologies can help the human being to open the new possibilities of the web. The papers, which contribute more to Web technologies, are published in Open Journal of Web Technologies (OJWT). https://www.ronpub.com/ojsw/OJSW_2015v2i1n02_Kachfah.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194879 In this paper we present BEAUFORD, a benchmark for methods which aim to provide formal expressions of concepts using the natural language (NL) definition of these concepts. Adding formal expressions of concepts to a given ontology allows reasoners to infer more useful pieces of information or to detect inconsistencies in this given ontology. To the best of our knowledge, BEAUFORD is the first benchmark to tackle this ontology enrichment problem. BEAUFORD allows the breaking down of a given formalisation approach by identifying its key features. In addition, BEAUFORD provides strong mechanisms to evaluate efficiently an approach even in case of ambiguity which is a major challenge in formalisation of NL resources. Indeed, BEAUFORD takes into account the fact that a given NL phrase can be formalised in many ways. Hence, it proposes a suitable specification to represent these multiple formalisations. Taking advantage of this specification, BEAUFORD redefines classical precision and recall and introduces other metrics to take into account the fact that there is not only one unique way to formalise a definition. Finally, BEAUFORD comprises a well-suited dataset to concretely judge of the efficiency of methods of formalisation. Using BEAUFORD, current approaches of formalisation of definitions can be compared accurately using a suitable gold standard. https://www.ronpub.com/ojsw/OJSW_2015v2i1n03_Blasko.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194898 Evolving ontologies by domain experts is difficult and typically cannot be performed without the assistance of an ontology engineer. This process takes long time and often recurrent modeling errors have to be resolved. This paper proposes a technique for creating controlled ontology evolution scenarios that ensure consistency of the possible ontology evolution and give guarrantees to the domain expert that his/her updates do not cause inconsistency. We introduce ontology templates that formalize the notion of controlled evolution and define ontology template consistency checking service together with a consistency checking algorithm. We prove correctness and demonstate the practical use of the techniques in two scenarios. https://www.ronpub.com/ojsw/OJSW_2015v2i1n04_Groppe.html http://nbn-resolving.de/urn:nbn:de:101:1-201705194910 Currently many SPARQL endpoints are freely available and accessible without any costs to users: Everyone can submit SPARQL queries to SPARQL endpoints via a standardized protocol, where the queries are processed on the datasets of the SPARQL endpoints and the query results are sent back to the user in a standardized format. As these distributed execution environments for semantic big data (as intersection of semantic data and big data) are freely accessible, the Semantic Web is an ideal playground for big data research. However, when utilizing these distributed execution environments, questions about the performance arise. Especially when several datasets (locally and those residing in SPARQL endpoints) need to be combined, distributed joins need to be computed. In this work we give an overview of the various possibilities of distributed join processing in SPARQL endpoints, which follow the SPARQL specification and hence are "W3C conform". We also introduce new distributed join approaches as variants of the Bitvector-Join and combination of the Semi- and Bitvector-Join. Finally we compare all the existing and newly proposed distributed join approaches for W3C conform SPARQL endpoints in an extensive experimental evaluation.