The importance of taking individual, potentially conflicting perspectives into account when dealing with knowledge has been widely recognised. Many existing ontology management approaches fully merge knowledge perspectives, which may require weakening in order to maintain consistency; others represent the distinct views in an entirely detached way. As an alternative, we propose Standpoint Logic, a simple, yet versatile multi-modal logic "add-on" for existing KR languages intended for the integrated representation of domain knowledge relative to diverse, possibly conflicting standpoints, which can be hierarchically organised, combined and put in relation to each other. Starting from the generic framework of First-Order Standpoint Logic (FOSL), we subsequently focus our attention on the fragment of sentential formulas, for which we provide a polytime translation into the standpoint-free version. This result yields decidability and favourable complexities for a variety of highly expressive decidable fragments of first-order logic. Using some elaborate encoding tricks, we then establish a similar translation for the very expressive description logic SROIQb_s underlying the OWL 2 DL ontology language. By virtue of this result, existing highly optimised OWL reasoners can be used to provide practical reasoning support for ontology languages extended by standpoint modelling.
翻译:在与知识打交道时,考虑个人、可能相互冲突的观点的重要性已经得到广泛承认。许多现有的本体管理方法完全融合了知识观点,这可能需要削弱知识观点,以便保持一致性;另一些则以完全独立的方式代表不同的观点。作为一种替代办法,我们提议对现有的KR语言采用Standpoint逻辑,这是简单而多功能的多式逻辑,目的是结合不同、可能相互冲突的观点,综合反映域知识,这些观点可以分等级排列、组合和相互关联。从OWL 2 DL 逻辑(OFSL)的通用框架开始,我们随后将注意力集中在发送公式的碎片上,为此,我们提供了一种多时间的翻译,将其翻译成到没有定位的版本。这样的结果产生了多种高度清晰易变的一阶逻辑碎片的可变性和有利复杂性。我们用一些复杂的编码技巧,然后为非常清晰的描述逻辑SROQb_s,作为OFL 2 DL 的理论基础,我们随后将注意力集中于发送的分解式公式。根据这一结果,现有高度偏化的OWL 理性用于推论的推论的推论可以扩大的推论。