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RonPub -- Research Online Publishing

RonPub (Research online Publishing) is an academic publisher of online, open access, peer-reviewed journals.  RonPub aims to provide a platform for researchers, developers, educators, and technical managers to share and exchange their research results worldwide.

RonPub is open access:

RonPub publishes all of its journals under the open access model, defined under BudapestBerlin, and Bethesda open access declarations:

  • All articles published by RonPub is fully open access and online available to readers free of charge.  
  • All open access articles are distributed under  Creative Commons Attribution License,  which permits unrestricted use, distribution and reproduction free of charge in any medium, provided that the original work is properly cited. 
  • Authors retain all copyright to their work.
  • Authors may also publish the publisher's version of their paper on any repository or website. 

RonPub is cost-effective:

To be able to provide open access journals, RonPub defray publishing cost by charging an one-time publication fee for each accepted article. One of RonPub objectives is providing a fast and high-quality but lower-cost publishing service. In order to ensure that the fee is never a barrier to publication, RonPub offers a fee waiver for authors who do not have funds to cover publication fees. We also offer a partial fee waiver for editors and reviewers of RonPub as as reward for their work. See the respective Journal webpage for the concrete publication fee.

RonPub Publication Ethics Statement:

In order to ensure the publishing quality and the reputation of the publisher, it is important that all parties involved in the act of publishing adhere to the standards of the publishing ethical behaviour. To verify the originality of submissions, we use Plagiarism Detection Tools, like Anti-Plagiarism, PaperRater, Viper, to check the content of manuscripts submitted to our journals against previous publications.

RonPub follows the Code of Conduct of the Committee on Publication Ethics (COPE), and deals with the cases of misconduct according to the COPE Flowcharts

Where is RonPub?

RonPub is a registered corporation in Lübeck, Germany. Lübeck is a beautiful harbour city, 60 kilometer away from Hamburg.

OJSW Cover
Open Journal of Semantic Web (OJSW)
OJSW, an open access and peer-reviewed online journal, publishes original and creative research results on the Semantic Web. OJSW distributes its articles under the open access model. All articles of OJSW are fully open access and online available to readers free of charge. There is no restriction on the length of the papers. Accepted manuscripts are published online immediately.
Publisher: RonPub UG (haftungsbeschränkt), Lübeck, Germany
Contact: OJSW Editorial Office
ISSN: 2199-336X
Call for Papers: txtUTF-8 txtASCII pdf
OJSW Cover
Open Journal of Semantic Web (OJSW)
OJSW, an open access and peer-reviewed online journal, publishes original and creative research results on the Semantic Web. OJSW distributes its articles under the open access model. All articles of OJSW are fully open access and online available to readers free of charge. There is no restriction on the length of the papers. Accepted manuscripts are published online immediately.
Publisher: RonPub UG (haftungsbeschränkt), Lübeck, Germany
Contact: OJSW Editorial Office
ISSN: 2199-336X
Call for Papers: txtUTF-8 txtASCII pdf

Aims & Scope

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.  

 OJSW publishes regular research papers, short communications, reviews and visionary papers in all aspects of web technologies. There is no restriction on the length of the papers. 

  • Regular research papers: being full original findings with adequate experimental research. They make substantial theoretical and empirical contributions to the research field.  Research papers should be written as concise as possible.
  • Short communications: reporting novel research ideas. The work represented should be technically sound and significantly advancing the state of the art. Short communications also include exploratory studies and methodological articles.
  • Research reviews: being insightful and accessible overview of a certain field of research. They conceptualize research issues, synthesize existing findings and advance the understanding of the field. They may also suggest new research issues and directions.
  • Visionary papers:  identify new research issues and future research directions, and describe new research visions in the field. The new visions will potentially have great impact for the future society and daily life. 

We are interested in scientific articles on all aspects of semantic web, including but are not limited to the following topics:

  • Semantic Data Management and Optimization
    • Big Data
    • Graph Databases
    • Federations
    • Spatial Data
  • Rule-based Languages like RIF and SWRL
  • Microformats (e.g. RDFa)
  • Ontology-based Approaches for
    • Modelling
    • Mapping
    • Evolution
    • Real-world ontologies
  • Reasoning Approaches
    • Real-World Applications
    • Efficient Algorithms
  • Linked Data
    • Integration of Heterogeneous Linked Data
    • Real-World Applications
    • Statistics and Visualizations
    • Quality
    • Ranking Techniques
    • Provenance
    • Mining and Consuming Linked Data
  • Semantic Web stream processing
    • Dynamic Data
    • Temporal Semantics
  • Performance and Evaluation of Semantic Web Technologies
    • Benchmarking for Semantic Web Technologies
  • Semantic Web Services
  • Semantic Web Applications in specific domains, e.g.,
    • Life Science,
    • eGovernment,
    • eEnvironment,
    • eHealth

Author Guidelines

Publication Criteria

Publication Criteria provides important information for authors to prepare their manuscripts with a high possibility of being accepted.

Open & Transparent Reviews

RonPub’s OJSW provides two review processes: open & transparent as well as traditional. OJSW authors and reviewers can choose the review process that they prefer.

  1. Open & Transparent Review:
    1. Submitted manuscripts are posted on the journal's website and are publicly available
      Names of authors can be blind: This depends on the authors’ wishes.
    2. Manuscripts will be evaluated by the reviewers selected by members of the editorial board.
    3. Manuscripts are also open for evaluation and comments from public.
      See our Open Review page for manuscripts currently under open review.
    4. Comments that do not follow established good scholarly practice will be removed.
    5. Evaluation from the selected reviewers and public participants will be posted on the journal’s website after the first-round review is finished.
      The names of reviewers and of public participants will not be given upon their wishes.
    6. The responses from the authors are posted on the journal’s website.
    7. Editors make a decision on acceptance or rejection based on the review results.
    8. Authors of rejected manuscripts may request to remove their articles and reviews from the journal’s website.
  2. Traditional Review:
    1. Manuscripts will be evaluated by the reviewers selected by members of the editorial board
    2. Editors make a decision on acceptance or rejection based on the review results.
    3. The decision and anonymous reviews of manuscripts will be sent to authors.

Manuscript Preparation

Please prepare your manuscripts using the manuscript template of the journal. It is available for download as word doc docx and latex version zip. The template describes the format and structure of manuscripts and other necessary information for preparing manuscripts. Manuscripts should be written in English. There is no restriction on the length of manuscripts.

Submission

Authors submit their manuscripts following the information on the submit pageAuthors first submit their manuscripts in PDF format. Once a manuscript is accepted, the author then submits the revised manuscript as a PDF file and a word file or latex folder (with all the material necessary to generate the PDF file). The work described in the submitted manuscript must be previously unpublished; it is not under consideration for publication anywhere else. 

Authors are welcome to suggest qualified reviewers for their papers, but this is not mandatory. If the author wants to do so, please provide the name, affiliations and e-mail addresses for all suggested reviewers.

Manuscript Status

After submission of manuscripts, authors will receive an email to confirm receipt of manuscripts. Subsequent enquiries concerning paper progress should be sent to the email address of the journal.

Review Procedure

RonPub is committed to enforcing a rigorous peer-review process. All manuscripts submitted for publication in RonPub journals are strictly and thoroughly peer-reviewed. Our editorial offices will organize the peer-reviewing and collect three review reports per manuscript. The editorial board will make an accept/revision/reject decision based on the reports of reviewers. Authors will be informed with the decision and reviewing results within 6-8 weeks after the manuscript submission. Authors should perform an adequate revision to address the concerns from reviewers. A second round of peer-review will be performed if necessary.

Accepted manuscripts are published online immediately.

Copyrights

Authors publishing with RonPub open journals retain the copyright to their work. 

All articles published by RonPub is fully open access and online available to readers free of charge.  RonPub publishes all open access articles under the Creative Commons Attribution License,  which permits unrestricted use, distribution and reproduction freely, provided that the original work is properly cited.

Articles of OJSW

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 Open Access 

Assessing and Improving Domain Knowledge Representation in DBpedia

Ludovic Font, Amal Zouaq, Michel Gagnon

Open Journal of Semantic Web (OJSW), 4(1), Pages 1-19, 2017, Downloads: 684

Full-Text: pdf | DOI: 10.19210/1006.4.1.1 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: With the development of knowledge graphs and the billions of triples generated on the Linked Data cloud, it is paramount to ensure the quality of data. In this work, we focus on one of the central hubs of the Linked Data cloud, DBpedia. In particular, we assess the quality of DBpedia for domain knowledge representation. Our results show that DBpedia has still much room for improvement in this regard, especially for the description of concepts and their linkage with the DBpedia ontology. Based on this analysis, we leverage open relation extraction and the information already available on DBpedia to partly correct the issue, by providing novel relations extracted from Wikipedia abstracts and discovering entity types using the dbo:type predicate. Our results show that open relation extraction can indeed help enrich domain knowledge representation in DBpedia.

BibTex:

    @Article{OJSW_2017v4i1n01_Font,
        title     = {Assessing and Improving Domain Knowledge Representation in DBpedia},
        author    = {Ludovic Font and
                     Amal Zouaq and
                     Michel Gagnon},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2017},
        volume    = {4},
        number    = {1},
        pages     = {1--19},
        url       = {https://www.ronpub.com/OJSW_2017v4i1n01_Font.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {With the development of knowledge graphs and the billions of triples generated on the Linked Data cloud, it is paramount to ensure the quality of data. In this work, we focus on one of the central hubs of the Linked Data cloud, DBpedia. In particular, we assess the quality of DBpedia for domain knowledge representation. Our results show that DBpedia has still much room for improvement in this regard, especially for the description of concepts and their linkage with the DBpedia ontology. Based on this analysis, we leverage open relation extraction and the information already available on DBpedia to partly correct the issue, by providing novel relations extracted from Wikipedia abstracts and discovering entity types using the dbo:type predicate. Our results show that open relation extraction can indeed help enrich domain knowledge representation in DBpedia.}
    }

 Open Access 

Hierarchical Multi-Label Classification Using Web Reasoning for Large Datasets

Rafael Peixoto, Thomas Hassan, Christophe Cruz, Aurélie Bertaux, Nuno Silva

Open Journal of Semantic Web (OJSW), 3(1), Pages 1-15, 2016, Downloads: 1246

Full-Text: pdf | DOI: 10.19210/1006.3.1.1 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: Extracting valuable data among large volumes of data is one of the main challenges in Big Data. In this paper, a Hierarchical Multi-Label Classification process called Semantic HMC is presented. This process aims to extract valuable data from very large data sources, by automatically learning a label hierarchy and classifying data items.The Semantic HMC process is composed of five scalable steps, namely Indexation, Vectorization, Hierarchization, Resolution and Realization. The first three steps construct automatically a label hierarchy from statistical analysis of data. This paper focuses on the last two steps which perform item classification according to the label hierarchy. The process is implemented as a scalable and distributed application, and deployed on a Big Data platform. A quality evaluation is described, which compares the approach with multi-label classification algorithms from the state of the art dedicated to the same goal. The Semantic HMC approach outperforms state of the art approaches in some areas.

BibTex:

    @Article{OJSW_2016v3i1n01_Peixoto,
        title     = {Hierarchical Multi-Label Classification Using Web Reasoning for Large Datasets},
        author    = {Rafael Peixoto and
                     Thomas Hassan and
                     Christophe Cruz and
                     Aur\'{e}lie Bertaux and
                     Nuno Silva},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {1--15},
        url       = {https://www.ronpub.com/OJSW_2016v3i1n01_Peixoto.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Extracting valuable data among large volumes of data is one of the main challenges in Big Data. In this paper, a Hierarchical Multi-Label Classification process called Semantic HMC is presented. This process aims to extract valuable data from very large data sources, by automatically learning a label hierarchy and classifying data items.The Semantic HMC process is composed of five scalable steps, namely Indexation, Vectorization, Hierarchization, Resolution and Realization. The first three steps construct automatically a label hierarchy from statistical analysis of data. This paper focuses on the last two steps which perform item classification according to the label hierarchy. The process is implemented as a scalable and distributed application, and deployed on a Big Data platform. A quality evaluation is described, which compares the approach with multi-label classification algorithms from the state of the art dedicated to the same goal. The Semantic HMC approach outperforms state of the art approaches in some areas.
}
    }

 Open Access 

A Semantic Question Answering Framework for Large Data Sets

Marta Tatu, Mithun Balakrishna, Steven Werner, Tatiana Erekhinskaya, Dan Moldovan

Open Journal of Semantic Web (OJSW), 3(1), Pages 16-31, 2016, Downloads: 1338

Full-Text: pdf | DOI: 10.19210/1006.3.1.16 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: Traditionally, the task of answering natural language questions has involved a keyword-based document retrieval step, followed by in-depth processing of candidate answer documents and paragraphs. This post-processing uses semantics to various degrees. In this article, we describe a purely semantic question answering (QA) framework for large document collections. Our high-precision approach transforms the semantic knowledge extracted from natural language texts into a language-agnostic RDF representation and indexes it into a scalable triplestore. In order to facilitate easy access to the information stored in the RDF semantic index, a user's natural language questions are translated into SPARQL queries that return precise answers back to the user. The robustness of this framework is ensured by the natural language reasoning performed on the RDF store, by the query relaxation procedures, and the answer ranking techniques. The improvements in performance over a regular free text search index-based question answering engine prove that QA systems can benefit greatly from the addition and consumption of deep semantic information.

BibTex:

    @Article{OJSW_2016v3i1n02_Tatu,
        title     = {A Semantic Question Answering Framework for Large Data Sets},
        author    = {Marta Tatu and
                     Mithun Balakrishna and
                     Steven Werner and
                     Tatiana Erekhinskaya and
                     Dan Moldovan},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {16--31},
        url       = {https://www.ronpub.com/OJSW_2016v3i1n02_Tatu.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Traditionally, the task of answering natural language questions has involved a keyword-based document retrieval step, followed by in-depth processing of candidate answer documents and paragraphs. This post-processing uses semantics to various degrees. In this article, we describe a purely semantic question answering (QA) framework for large document collections. Our high-precision approach transforms the semantic knowledge extracted from natural
language texts into a language-agnostic RDF representation and indexes it into a scalable triplestore. In order to facilitate easy access to the information stored in the RDF semantic index, a user's natural language questions are translated into SPARQL queries that return precise answers back to the user. The robustness of this framework is ensured by the natural language reasoning performed on the RDF store, by the query relaxation procedures, and the answer ranking techniques. The improvements in performance over a regular free text search index-based question answering engine prove that QA systems can benefit greatly from the addition and consumption of deep semantic information.}
    }

 Open Access 

OnGIS: Semantic Query Broker for Heterogeneous Geospatial Data Sources

Marek Smid, Petr Kremen

Open Journal of Semantic Web (OJSW), 3(1), Pages 32-50, 2016, Downloads: 856

Full-Text: pdf | DOI: 10.19210/1006.3.1.32 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: Querying geospatial data from multiple heterogeneous sources backed by different management technologies poses an interesting problem in the data integration and in the subsequent result interpretation. This paper proposes broker techniques for answering a user's complex spatial query: finding relevant data sources (from a catalogue of data sources) capable of answering the query, eventually splitting the query and finding relevant data sources for the query parts, when no single source suffices. For the purpose, we describe each source with a set of prototypical queries that are algorithmically arranged into a lattice, which makes searching efficient. The proposed algorithms leverage GeoSPARQL query containment enhanced with OWL 2 QL semantics. A prototype is implemented in a system called OnGIS.

BibTex:

    @Article{OJSW_2016v3i1n03_Smid,
        title     = {OnGIS: Semantic Query Broker for Heterogeneous Geospatial Data Sources},
        author    = {Marek Smid and
                     Petr Kremen},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2016},
        volume    = {3},
        number    = {1},
        pages     = {32--50},
        url       = {https://www.ronpub.com/OJSW_2016v3i1n03_Smid.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Querying geospatial data from multiple heterogeneous sources backed by different management technologies poses an interesting problem in the data integration and in the subsequent result interpretation. This paper proposes broker techniques for answering a user's complex spatial query: finding relevant data sources (from a catalogue of data sources) capable of answering the query, eventually splitting the query and finding relevant data sources for the query parts, when no single source suffices. For the purpose, we describe each source with a set of prototypical queries that are algorithmically arranged into a lattice, which makes searching efficient. The proposed algorithms leverage GeoSPARQL query containment enhanced with OWL 2 QL semantics. A prototype is implemented in a system called OnGIS.}
    }

 Open Access 

Semantic and Web: The Semantic Part

Sven Groppe, Paulo Rupino da Cunha

Open Journal of Semantic Web (OJSW), 2(1), Pages 1-3, 2015, Downloads: 1212

Full-Text: pdf | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: 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).

BibTex:

    @Article{OJSW_2015v2i1n01e_Groppe,
        title     = {Semantic and Web: The Semantic Part},
        author    = {Sven Groppe and
                     Paulo Rupino da Cunha},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {1--3},
        url       = {https://www.ronpub.com/OJSW_2015v2i1n01e_Groppe.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {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).}
    }

 Open Access 

BEAUFORD: A Benchmark for Evaluation of Formalisation of Definitions in OWL

Cheikh Kacfah Emani, Catarina Ferreira Da Silva, Bruno Fiés, Parisa Ghodous

Open Journal of Semantic Web (OJSW), 2(1), Pages 4-15, 2015, Downloads: 810

Full-Text: pdf | DOI (reserved): 10.19210/1006.2.1.4 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: 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.

BibTex:

    @Article{OJSW_2015v2i1n02_Kachfah,
        title     = {BEAUFORD: A Benchmark for Evaluation of
Formalisation of Definitions in OWL},
        author    = {Cheikh Kacfah Emani and
                     Catarina Ferreira Da Silva and
                     Bruno Fi\'{e}s and
                     Parisa Ghodous},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {4--15},
        url       = {https://www.ronpub.com/OJSW_2015v2i1n02_Kachfah.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {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.}
    }

 Open Access 

Ontology Evolution Using Ontology Templates

Miroslav Blasko, Petr Kremen, Zdenek Kouba

Open Journal of Semantic Web (OJSW), 2(1), Pages 16-29, 2015, Downloads: 685

Full-Text: pdf | DOI: 10.19210/1006.2.1.16 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: 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.

BibTex:

    @Article{OJSW_2015v2i1n03_Blasko,
        title     = {Ontology Evolution Using Ontology Templates},
        author    = {Miroslav Blasko and
                     Petr Kremen and
                     Zdenek Kouba},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {16--29},
        url       = {https://www.ronpub.com/OJSW_2015v2i1n03_Blasko.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {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.}
    }

 Open Access 

Distributed Join Approaches for W3C-Conform SPARQL Endpoints

Sven Groppe, Dennis Heinrich, Stefan Werner

Open Journal of Semantic Web (OJSW), 2(1), Pages 30-52, 2015, Downloads: 1204

Full-Text: pdf | DOI (reserved): 10.19210/1006.2.1.30 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Presentation: Video

Abstract: 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.

BibTex:

    @Article{OJSW_2015v2i1n04_Groppe,
        title     = {Distributed Join Approaches for W3C-Conform SPARQL Endpoints},
        author    = {Sven Groppe and
                     Dennis Heinrich and
                     Stefan Werner},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2015},
        volume    = {2},
        number    = {1},
        pages     = {30--52},
        url       = {https://www.ronpub.com/OJSW_2015v2i1n04_Groppe.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {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.}
    }

 Open Access 

Developing Knowledge Models of Social Media: A Case Study on LinkedIn

Jinwu Li, Vincent Wade, Melike Sah

Open Journal of Semantic Web (OJSW), 1(2), Pages 1-24, 2014, Downloads: 2502

Full-Text: pdf | DOI: 10.19210/OJSW-v1i2n01_Li | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: User Generated Content (UGC) exchanged via large Social Network is considered a very important knowledge source about all aspects of the social engagements (e.g. interests, events, personal information, personal preferences, social experience, skills etc.). However this data is inherently unstructured or semi-structured. In this paper, we describe the results of a case study on LinkedIn Ireland public profiles. The study investigated how the available knowledge could be harvested from LinkedIn in a novel way by developing and applying a reusable knowledge model using linked open data vocabularies and semantic web. In addition, the paper discusses the crawling and data normalisation strategies that we developed, so that high quality metadata could be extracted from the LinkedIn public profiles. Apart from the search engine in LinkedIn.com itself, there are no well known publicly available endpoints that allow users to query knowledge concerning the interests of individuals on LinkedIn. In particular, we present a system that extracts and converts information from raw web pages of LinkedIn public profiles into a machine-readable, interoperable format using data mining and Semantic Web technologies. The outcomes of our research can be summarized as follows: (1) A reusable knowledge model which can represent LinkedIn public users and company profiles using linked data vocabularies and structured data, (2) a public SPARQL endpoint to access structured data about Irish industry and public profiles, (3) a scalable data crawling strategy and mashup based data normalisation approach. The proposed data mining and knowledge representation proposed in this paper are evaluated in four ways: (1) We evaluate metadata quality using automated techniques, such as data completeness and data linkage. (2) Data accuracy is evaluated via user studies. In particular, accuracy is evaluated by comparison of manually entered metadata fields and the metadata which was automatically extracted. (3) User perceived metadata quality is measured by asking users to rate the automatically extracted metadata in user studies. (4) Finally, the paper discusses how the extracted metadata suits for a user interface design. Overall, the evaluations show that the extracted metadata is of high quality and meets the requirements of a data visualisation user interface.

BibTex:

    @Article{OJSW-v1i2n01_Li,
        title     = {Developing Knowledge Models of Social Media: A Case Study on LinkedIn},
        author    = {Jinwu Li and
                     Vincent Wade and
                     Melike Sah},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {1--24},
        url       = {https://www.ronpub.com/OJSW-v1i2n01_Li.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {User Generated Content (UGC) exchanged via large Social Network is considered a very important knowledge source about all aspects of the social engagements (e.g. interests, events, personal information, personal preferences, social experience, skills etc.). However this data is inherently unstructured or semi-structured. In this paper, we describe the results of a case study on LinkedIn Ireland public profiles. The study investigated how the available knowledge could be harvested from LinkedIn in a novel way by developing and applying a reusable knowledge model using linked open data vocabularies and semantic web. In addition, the paper discusses the crawling and data normalisation strategies that we developed, so that high quality metadata could be extracted from the LinkedIn public profiles. Apart from the search engine in LinkedIn.com itself, there are no well known publicly available endpoints that allow users to query knowledge concerning the interests of individuals on LinkedIn. In particular, we present a system that extracts and converts information from raw web pages of LinkedIn public profiles into a machine-readable, interoperable format using data mining and Semantic Web technologies. The outcomes of our research can be summarized as follows: (1) A reusable knowledge model which can represent LinkedIn public users and company profiles using linked data vocabularies and structured data, (2) a public SPARQL endpoint to access structured data about Irish industry and public profiles, (3) a scalable data crawling strategy and mashup based data normalisation approach. The proposed data mining and knowledge representation proposed in this paper are evaluated in four ways: (1) We evaluate metadata quality using automated techniques, such as data completeness and data linkage. (2) Data accuracy is evaluated via user studies. In particular, accuracy is evaluated by comparison of manually entered metadata fields and the metadata which was automatically extracted. (3) User perceived metadata quality is measured by asking users to rate the automatically extracted metadata in user studies. (4) Finally, the paper discusses how the extracted metadata suits for a user interface design. Overall, the evaluations show that the extracted metadata is of high quality and meets the requirements of a data visualisation user interface.}
    }

 Open Access 

P-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud

Sven Groppe, Thomas Kiencke, Stefan Werner, Dennis Heinrich, Marc Stelzner, Le Gruenwald

Open Journal of Semantic Web (OJSW), 1(2), Pages 25-55, 2014, Downloads: 1997

Full-Text: pdf | DOI (reserved): 10.19210/1006.1.2.25 | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Presentation: Video

Abstract: Increasingly data on the Web is stored in the form of Semantic Web data. Because of today's information overload, it becomes very important to store and query these big datasets in a scalable way and hence in a distributed fashion. Cloud Computing offers such a distributed environment with dynamic reallocation of computing and storing resources based on needs. In this work we introduce a scalable distributed Semantic Web database in the Cloud. In order to reduce the number of (unnecessary) intermediate results early, we apply bloom filters. Instead of computing bloom filters, a time-consuming task during query processing as it has been done traditionally, we precompute the bloom filters as much as possible and store them in the indices besides the data. The experimental results with data sets up to 1 billion triples show that our approach speeds up query processing significantly and sometimes even reduces the processing time to less than half.

BibTex:

    @Article{OJSW-v1i2n02_Groppe,
        title     = {P-LUPOSDATE: Using Precomputed Bloom Filters to Speed Up SPARQL Processing in the Cloud},
        author    = {Sven Groppe and
                     Thomas Kiencke and
                     Stefan Werner and
                     Dennis Heinrich and
                     Marc Stelzner and
                     Le Gruenwald},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {2},
        pages     = {25--55},
        url       = {https://www.ronpub.com/OJSW-v1i2n02_Groppe.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Increasingly data on the Web is stored in the form of Semantic Web data. Because of today's information overload, it becomes very important to store and query these big datasets in a scalable way and hence in a distributed fashion. Cloud Computing offers such a distributed environment with dynamic reallocation of computing and storing resources based on needs. In this work we introduce a scalable distributed Semantic Web database in the Cloud. In order to reduce the number of (unnecessary) intermediate results early, we apply bloom filters. Instead of computing bloom filters, a time-consuming task during query processing as it has been done traditionally, we precompute the bloom filters as much as possible and store them in the indices besides the data. The experimental results with data sets up to 1 billion triples show that our approach speeds up query processing significantly and sometimes even reduces the processing time to less than half.}
    }

 Open Access 

MapReduce-based Solutions for Scalable SPARQL Querying

José M. Giménez-Garcia, Javier D. Fernández, Miguel A. Martínez-Prieto

Open Journal of Semantic Web (OJSW), 1(1), Pages 1-18, 2014, Downloads: 2097

Full-Text: pdf | DOI: 10.19210/OJSW-v1i1n02_Garcia | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and rconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results.

BibTex:

    @Article{OJSW-v1i1n02_Garcia,
        title     = {MapReduce-based Solutions for Scalable SPARQL Querying},
        author    = {Jos\'{e} M. Gim\'{e}nez-Garcia and
                     Javier D. Fern\'{a}ndez and
                     Miguel A. Mart\'{i}nez-Prieto},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {1--18},
        url       = {https://www.ronpub.com/OJSW-v1i1n02_Garcia.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and rconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among the distributed solutions facing RDF scalability issues. In this article, we survey the most important works addressing RDF management and querying through diverse MapReduce approaches, with a focus on their main strategies, optimizations and results.}
    }

 Open Access 

BioSStore: A Client Interface for a Repository of Semantically Annotated Bioinformatics Web Services

Ismael Navas-Delgado, José F. Aldana-Montes

Open Journal of Semantic Web (OJSW), 1(1), Pages 19-29, 2014, Downloads: 1852

Full-Text: pdf | DOI: 10.19210/OJSW-v1i1n03_Delgado | Meta-Data: tex xml rdf rss | Show/Hide Abstract | Show/Hide BibTex

Abstract: Bioinformatics has shown itself to be a domain in which Web services are being used extensively. In this domain, simple but real services are being developed. Thus, there are huge repositories of real services available (for example BioMOBY main repository includes more than 1500 services). Besides, bioinformatics repositories usually have active communities using and working on improvements. However, these kinds of repositories do not exploit the full potential of Web services (and SOA, Service Oriented Applications, in general). On the other hand, sophisticated technologies have been proposed to improve SOA, including the annotation on Web services to explicitly describe them. However, these approaches are lacking in repositories with real services. In the work presented here, we address the drawbacks present in bioinformatics services and try to improve the current semantic model by introducing the use of the W3C standard Semantic Annotations for WSDL and XML Schema (SAWSDL) and related proposals (WSMO Lite). This paper focuses on a user interface that takes advantage of a repository of semantically annotated bioinformatics Web services. In this way, we exploit semantics for the discovery of Web services, showing how the use of semantics will improve the user searches. The BioSStore is available at http://biosstore.khaos.uma.es. This portal will contain also future developments of this proposal.

BibTex:

    @Article{OJSW-v1i1n03_Delgado,
        title     = {BioSStore: A Client Interface for a Repository of Semantically Annotated Bioinformatics Web Services},
        author    = {Ismael Navas-Delgado and
                     Jos\'{e} F. Aldana-Montes},
        journal   = {Open Journal of Semantic Web (OJSW)},
        issn      = {2199-336X},
        year      = {2014},
        volume    = {1},
        number    = {1},
        pages     = {19--29},
        url       = {https://www.ronpub.com/OJSW-v1i1n03_Delgado.pdf},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Bioinformatics has shown itself to be a domain in which Web services are being used extensively. In this domain, simple but real services are being developed. Thus, there are huge repositories of real services available (for example BioMOBY main repository includes more than 1500 services). Besides, bioinformatics repositories usually have active communities using and working on improvements. However, these kinds of repositories do not exploit the full potential of Web services (and SOA, Service Oriented Applications, in general). On the other hand, sophisticated technologies have been proposed to improve SOA, including the annotation on Web services to explicitly describe them. However, these approaches are lacking in repositories with real services. In the work presented here, we address the drawbacks present in bioinformatics services and try to improve the current semantic model by introducing the use of the W3C standard Semantic Annotations for WSDL and XML Schema (SAWSDL) and related proposals (WSMO Lite). This paper focuses on a user interface that takes advantage of a repository of semantically annotated bioinformatics Web services. In this way, we exploit semantics for the discovery of Web services, showing how the use of semantics will improve the user searches. The BioSStore is available at http://biosstore.khaos.uma.es. This portal will contain also future developments of this proposal.}
    }

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Editors and reviewers have no access to payment information. The inability to pay will not influence the decision to publish a paper; decisions to publish are only based on the quality of work and the editorial criteria.

OJSW Indexing

In order for our publications getting widely abstracted, indexed and cited, the following methods are employed:

  • Various meta tags are embedded in each publication webpage, including Google Scholar Tags, Dublic Core, EPrints, BE Press and Prism. This enables crawlers of e.g. Google Scholar to discover and index our publications.
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The paper Getting Indexed by Bibliographic Databases in the Area of Computer Science provides a comprehensive survey on indexing formats, techniques and databases. We will also continue our efforts on dissemination and indexing of our publications.

OJSW has been indexed by the following libraries and bibliographic databases:

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For authors: Authors should present their work honestly without fabrication, falsification, plagiarism or inappropriate data manipulation.

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In order to filter fabricated submissions, the editorial office will check the authenticity of the authors and their affiliations before a peer-review begins. It is important that the authors communicate with us using the email addresses of their affiliations and provide us the URL addresses of their affiliations. The overall quality of paper will be also checked including format, figures, tables, integrity and adequacy. Authors may be required to improve the quality of their paper before sending it out for review. If a paper is obviously of low quality, the paper will be directly rejected.

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For a contribution to be acceptable for publication, these points should be at least in middle level.

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