iTract: Islands of Tractability in Ontology-Based Data Access

15年前，大多数数据都是结构化的、完整的，并在数据库中组织得井然有序。情况已经不再是这样了。非结构化、不完整和异质的数据集正在以惊人的速度激增。这在万维网的背景下最为明显，但也适用于科学数据、商业和工业数据、医疗保健数据和许多其他领域的数据。为了利用这些数据，基于标准数据库技术的传统信息系统已不再足够。基于本体的数据访问和管理是解决这一挑战的一种新方法，它引入了语义层(本体)，为用户提供了数据的高级统一视图以及用于访问和查询数据的词汇表。本体通过提供术语和它们之间的关系的机器可读定义来对应用领域建模。它们已经在许多应用中使用，例如，NHS：为了使英国和世界各地的卫生专业人员能够进行交流，他们使用相同的术语是至关重要的；这样的术语由本体SNOMED CT提供。使用本体来访问数据，从而直接将数据和知识结合在一起是21世纪的一个新想法。首先，应用表明，基于本体的数据访问和管理确实是可行的，并具有彻底改变现代信息系统的潜力。然而，使用可表达的本体语言进行查询应答的可扩展性仍然是一个巨大的挑战，本项目的目标是开发一种新的“可处理性孤岛”方法来解决这一问题。我们的方法将基于本体的数据访问与计算机科学的两个成熟和成功的领域联系起来：约束满足和布尔电路复杂性。我们的目标是将证明方法、技术和方法论从这两个领域转移到基于本体的数据访问。这包括非均匀复杂性分析，其中我们的目标是对回答本体中介的查询的复杂性进行分类，该查询由本体和标准数据库查询组成。基于这种复杂性分析，我们将为识别出的易处理的本体中介查询孤岛开发出统一高效的查询回答算法，并在基于本体的数据访问系统On Top和Combo中实现它们。我们将把我们的新技术应用于石油和天然气行业以及医疗保健领域的案例研究。

15 years ago most data was structured, complete, and neatly organised in databases. This is no longer the case. Unstructured, incomplete, and heterogeneous data sets are proliferating at an enormous rate. This is most evident in the context of the World Wide Web, but also applies to scientific data, data in business and industry, data in healthcare and in many other areas. To make use of such data, traditional information systems based on standard database technologies are no longer sufficient. Ontology-based data access and management is a novel approach to address this challenge by introducing a semantic layer (ontology) that provides the user with a high-level unified view of the data as well as a vocabulary to access and query the data. Ontologies model application domains by providing machine readable definitions of terms and relationships between them. They are already used in numerous applications, for example, by the NHS: to enable communication between health professionals within the United Kingdom and worldwide, it is crucial that they use the same terminology; such a terminology is provided by the ontology SNOMED CT.Using ontologies to access data and thereby directly combining data and knowledge is a novel idea of the 21st century. First applications have demonstrated that ontology-based data access and management is indeed feasible and has the potential to revolutionise modern information systems. However, scalability of query answering with expressive ontology languages remains a big challenge, and it is the aim of this project to develop a new "island of tractability" approach to tackle it. Our approach links ontology-based data access with two well-established and successful areas of Computer Science: constraint satisfaction and Boolean circuit complexity. We aim to transfer proof methods, techniques, and methodologies from these two areas to ontology-based data access. This includes a non-uniform complexity analysis, where we aim to classify the complexity of answering ontology-mediated queries, which consist of an ontology and a standard database query. Based on this complexity analysis, we will develop uniformly efficient query answering algorithms for the identified islands of tractable ontology-mediated queries, and implement them in the ontology-based data access systems Ontop and Combo. We will apply our novel technology to case studies from oil and gas industry and healthcare.