  In recent years, technologies of indoor crowd positioning and movement data
analysis have received widespread attention in the fields of reliability
management, indoor navigation, and crowd behavior monitoring. However, only a
few indoor crowd movement trajectory datasets are available to the public, thus
restricting the development of related research and application. This paper
contributes a new benchmark dataset of indoor crowd movement trajectories. This
dataset records the movements of over 5000 participants at a three day large
academic conference in a two story indoor venue. The conference comprises
varied activities, such as academic seminars, business exhibitions, a hacking
contest, interviews, tea breaks, and a banquet. The participants are divided
into seven types according to participation permission to the activities. Some
of them are involved in anomalous events, such as loss of items, unauthorized
accesses, and equipment failures, forming a variety of spatial temporal
movement patterns. In this paper, we first introduce the scenario design,
entity and behavior modeling, and data generator of the dataset. Then, a
detailed ground truth of the dataset is presented. Finally, we describe the
process and experience of applying the dataset to the contest of ChinaVis Data
Challenge 2019. Evaluation results of the 75 contest entries and the feedback
from 359 contestants demonstrate that the dataset has satisfactory
completeness, and usability, and can effectively identify the performance of
methods, technologies, and systems for indoor trajectory analysis.
