Levin Mikhail K, Cowell Lindsay G
Department of Clinical Sciences, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX USA.
J Biomed Semantics. 2015 Sep 16;6:35. doi: 10.1186/s13326-015-0035-z. eCollection 2015.
The increasing use of ontologies highlights the need for a library for working with ontologies that is efficient, accessible from various programming languages, and compatible with common computational platforms.
We developed owlcpp, a library for storing and searching RDF triples, parsing RDF/XML documents, converting triples into OWL axioms, and reasoning. The library is written in ISO-compliant C++ to facilitate efficiency, portability, and accessibility from other programming languages. Internally, owlcpp uses the Raptor RDF Syntax library for parsing RDF/XML and the FaCT++ library for reasoning. The current version of owlcpp is supported under Linux, OSX, and Windows platforms and provides an API for Python.
The results of our evaluation show that, compared to other commonly used libraries, owlcpp is significantly more efficient in terms of memory usage and searching RDF triple stores. owlcpp performs strict parsing and detects errors ignored by other libraries, thus reducing the possibility of incorrect semantic interpretation of ontologies. owlcpp is available at http://owl-cpp.sf.net/ under the Boost Software License, Version 1.0.
本体的使用日益增加,这凸显了对一个用于处理本体的库的需求,该库应高效、可从多种编程语言访问并与常见计算平台兼容。
我们开发了owlcpp,这是一个用于存储和搜索RDF三元组、解析RDF/XML文档、将三元组转换为OWL公理以及进行推理的库。该库用符合ISO标准的C++编写,以提高效率、可移植性并便于从其他编程语言访问。在内部,owlcpp使用Raptor RDF语法库来解析RDF/XML,并使用FaCT++库进行推理。owlcpp的当前版本在Linux、OSX和Windows平台上得到支持,并为Python提供了一个应用程序编程接口。
我们的评估结果表明,与其他常用库相比,owlcpp在内存使用和搜索RDF三元组存储方面显著更高效。owlcpp进行严格的解析并检测其他库忽略的错误,从而降低了对本体进行错误语义解释的可能性。owlcpp可在http://owl-cpp.sf.net/ 上获取,遵循Boost软件许可协议1.0版。