论文标题
行为数据的结构
The structure of behavioral data
论文作者
论文摘要
一个多世纪以来，科学家一直在收集行为数据 - 现在，越来越多的部分正在公开共享，以便其他研究人员可以重复使用它们来复制，整合或扩展过去的结果。尽管行为数据是许多科学领域的基础，但目前尚无广泛采用的标准用于格式化，命名，组织，描述或共享此类数据。缺乏标准化是科学进步的主要瓶颈。它不仅可以防止数据的有效重复使用，还会影响一般行为数据的处理方式，因为非标准数据调用了定制数据分析代码并防止开发有效的工具。为了解决这个问题，我们开发了构造行为数据的标准，我们开发了Behaverse数据模型（BDM）。在这里，我们专注于行为数据中的主要概念，留下了项目网站（https://behaverse.github.io/data-model/）的更多详细信息和发展。
For more than a century, scientists have been collecting behavioral data--an increasing fraction of which is now being publicly shared so other researchers can reuse them to replicate, integrate or extend past results. Although behavioral data is fundamental to many scientific fields, there is currently no widely adopted standard for formatting, naming, organizing, describing or sharing such data. This lack of standardization is a major bottleneck for scientific progress. Not only does it prevent the effective reuse of data, it also affects how behavioral data in general are processed, as non-standard data calls for custom-made data analysis code and prevents the development of efficient tools. To address this problem, we develop the Behaverse Data Model (BDM), a standard for structuring behavioral data. Here we focus on major concepts in behavioral data, leaving further details and developments to the project's website (https://behaverse.github.io/data-model/).
