ABSTRACT

Question Answering (QA), the process of computing valid answers to questions formulated in natural language, has recently gained attention in both industry and academia. Translating this idea to the realm of geographic information systems (GIS) may open new opportunities for data scientists. In theory, analysts may simply ask spatial questions to exploit diverse geographic information resources, without a need to know how GIS tools and geodata sets interoperate. In this outlook article, we investigate the scientific challenges of geo-analytical question answering, introducing the problems of unknown answers and indirect QA. Furthermore, we argue why core concepts of spatial information play an important role in addressing this challenge, enabling us to describe analytic potentials, and to compose spatial questions and workflows for generating answers.

摘要

问题解答（QA）是计算以自然语言提出的问题的有效答案的过程，最近在业界和学术界都受到关注。将这一想法转化为地理信息系统（GIS）的领域可能为数据科学家带来新的机会。从理论上讲，分析人员只需提出空间问题即可开发各种地理信息资源，而无需了解GIS工具和地理数据集如何互操作。在这篇前瞻性文章中，我们调查了地理分析问题解答的科学挑战，介绍了未知答案和间接质量检查的问题。此外，我们争论了为什么空间信息的核心概念 在应对这一挑战方面发挥着重要作用，使我们能够描述分析潜力，并组成空间问题和工作流以生成答案。