Recently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future.

最近，作为有效保存和传播研究数据的先决条件，研究数据管理的主题出现在开放科学的前沿。与此同时，科学实验室仍然依靠由实验者处理的数字文件来分析和交流实验室结果。在这项研究中，我们首先应用取证过程来调查作为已发表结果的数字证据的信息质量。此外，我们使用符号学来描述使用实验室取证技术从存储系统中恢复的信息的质量。接下来，我们根据取证分析的结果制定实验室分析能力。实验室取证和分析构成了研究数据管理的基础。最后，我们提出了开放科学准备的概念概述，