Reasoning with Uncertainty and Inconsistency in Structured Scientific Knowledge

在各种在线资源中，科学家可以获得的信息数量巨大且迅速增加。然而，这些丰富的信息给那些希望定位和分析来自不同来源的知识的科学家带来了挑战。存在的关键问题是，个别科学知识来源存在很大的不确定性，不同科学知识来源之间产生了许多冲突。因此，科学家需要能够容忍不确定性和不一致性的工具，以便查询和合并科学知识。本项目旨在通过结构化科学知识（SSK）技术的发展促进科学知识的分析。SSK由一组SSK报告表示，每个报告都是描述一个或多个科学数据源（如一篇或多篇期刊文章、经验数据集等）的结构化报告。该格式是一个XML文档，其文本限制为科学术语中的单个单词、值或简单短语。SSK旨在帮助科学家理解数据源的内容。每一个都包含关于数据源的摘要信息（例如，来自摘要的信息，所使用技术的摘要等）以及关于数据源的评估信息(例如：描述信息来源中的不确定性和错误，关键发现的资格等)。摘要信息描述了数据源作者提供的信息，评估信息描述了数据源的用户或作者提供的信息。SSK可以通过手工、信息提取技术和分析数据源来构建。在这个项目中，我们希望通过利用形式理论来表示和推理不确定和不一致的信息，来扩展我们现有的合并和分析异构结构化信息的工作。该项目的结果将是一个通用的理论框架，用于处理SSK中的不确定性和不一致性，并在原型实现中演示该框架，用于查询和合并来自异构源的潜在冲突SSK。

There is a huge and rapidly expanding amount of information available for scientists in various online resources. However, this wealth of information has created challenges for scientists who wish to locate and analyse knowledge from heterogeneous sources. Key problems that exist are that there is much uncertainty in individual sources of scientific knowledge, and many conflicts arising between different sources of scientific knowledge. Scientists therefore need tools that are tolerant of uncertainty and inconsistency in order to query and merge scientific knowledge.This project aims to facilitate the analysis of scientific knowledge by the development of technology for structured scientific knowledge (SSK). SSK is represented by a set of SSK reports each of which is a structured report that describes one or more scientific datasources (such as one or more journal articles, empirical datasets, etc). The format is an XML document with textentries restricted to individual words, values or simple phrases in scientific terminology. SSK is intended to help scientists understand the contents of a datasource. Each one contains summaritive information about the datasource (e.g. information from an abstract, summary of techniques used, etc) plus evaluative information about the datasource (eg. delineation of uncertainties and errors in the information source, qualifications of the key findings, etc). The summaritive information describes the information provided by the authors of the datasource, and the evaluative information describes the information provided by the users or authors of the datasource. SSK can be constructed by hand, by information extraction technology, and as a result of analysing datasources. In this project, we want to extend our existing work for merging and analysing heterogeneous structured information by harnessing formal theories for representing and reasoning with uncertain and inconsistent information. The result of the project will be a general theoretical framework for handling uncertainty and inconsistency in SSK, and a demonstration of the framework in a prototype implementation for querying and merging potentially conflicting SSK from heterogeneous sources.