Processing Queries over Conceptual Integration Schemas

商业智能（BI）是一个软件行业术语，指的是在组织内使用信息，使决策者（通常是执行人员）能够做出明智的决策，并使用已知数据有效地运行操作。作为计算机科学的一个研究领域，它包含了计算机科学的几个子领域，其中数据集成（即数据仓库）起着举足轻重的作用。理想情况下，集成几乎是自动进行的。BI的一个重要目标是面向最终用户：决策者和业务用户只需要专注于用他们完全理解的业务术语（通常是高级的）建模他们的数据需求。业务用户将指定需要什么信息和以什么形式，集成系统将通过尽可能自动地生成集成数据来满足请求。要实现这一点，我们必须显著提高抽象级别以适应业务用户。后者将使用概念级模式对其集成需求进行建模。一旦这些模式就位，业务用户就可以针对这些概念模式提出用概念查询语言表达的查询。基于之前关于概念集成模式建模的工作，本提案的目标如下：(1)解决回答关于概念集成模式的业务查询的问题；(2)识别和研究具有实际重要性的可处理的查询类别；(3)为其中一些易于处理的类开发和实现有效的算法。

Business intelligence (BI) is a software industry term that denotes the use of information within organizations to allow deciders, usually executives, to make informed decisions, and to effectively run operations using known data. As a Computer Science research field, it encompasses several subfields of Computer Science, among which data integration (aka data warehousing) plays a pivotal role. Ideally, integration would happen almost automatically. One important aim of BI is to be end-user oriented: decision makers and business users need only to focus on modelling their data needs in (usually high-level ) business terms that they fully understand. A business user would specify what information is needed and in what form, and the integration system would satisfy the request by producing integrated data as automatically as possible. To achieve this, we must raise the level of abstraction significantly to accommodate business users. The latter would use conceptual-level schemas to model their integration needs. Once those schemas are in place, business users can pose queries expressed in a conceptual query language against those conceptual schemas. Building on previous work on conceptual integration schema modelling, the objectives of the present proposal are as follows: (1) address the problem of answering business queries over conceptual integration schemas; (2) identify and study tractable classes of queries that are of practical importance; (3) develop and implement efficient algorithms for some of those tractable classes.