How can metadata improve the discoverability of laboratory data?

1 Why metadata matters

Metadata matters because it helps you and others to understand and use your data. Without metadata, your data might be meaningless, incomplete, or inaccessible. For example, if you have a spreadsheet of measurements, but you don't know what they represent, how they were obtained, or what units they use, you won't be able to interpret or analyze them. Metadata can also help you to organize, document, and archive your data, making it easier to find and retrieve later. Moreover, metadata can enhance the visibility and impact of your data, by enabling search engines, databases, and repositories to index and link your data to other relevant resources.

2 What metadata to include

The type, size, complexity, and purpose of your data, as well as the standards and requirements of your field or discipline and the platforms and tools used to store and share your data, all affect the metadata you include. Common elements of metadata include an identifier (unique and persistent code or name), a title (concise and descriptive name summarizing your data), the creator (name and affiliation of the person or entity who produced or collected the data), date (date or range of dates when the data was created or modified), description (brief explanation of the nature, scope, and content of your data), format (file type, extension, or structure of your data), rights (terms and conditions governing access and use of your data such as licenses or permissions), relation (connection to other related data or resources such as publications, datasets, or projects), subject (keywords, topics, or concepts describing your data), and source (origin or provenance such as instrument, method, or protocol used to generate or collect it).

3 How to create metadata

Creating metadata for your data can be done in various ways, depending on the level of detail and automation you require. The manual method, which involves entering the information in a text file, a spreadsheet, or a form, offers more control and flexibility. However, it can be time-consuming and prone to errors. Alternatively, you could use software or tools to generate metadata automatically based on predefined rules or templates. This method is fast and consistent, but may not be accurate or comprehensive enough. Finally, semi-automatic methods involve using software or tools that can extract some metadata from your data files automatically and allow you to edit or add more information. This option may save time and effort, but it could fail to capture all relevant metadata or follow the standards of your field or discipline.

4 How to manage metadata

Once you have created metadata for your data, it is essential to manage it properly to ensure its quality, consistency, and usability. Some best practices for managing metadata include validating the data against standards and specifications, updating it as the data changes over time, storing it in a secure and accessible location, and sharing it with others in a catalog, database, or repository. Doing so can help identify and correct errors, make sure the metadata is current and relevant, preserve and protect the metadata, increase discoverability and visibility of the data, and enable its reuse and citation.

5 How to use metadata

Finally, you can use metadata to improve the discoverability of laboratory data for yourself and others. This includes searching, accessing, reusing, and citing data. Searching allows you to find data that meets your criteria or interests, either within your own collection or across different sources. You can also filter, sort, or rank the results of your search based on the attributes or values of the metadata. Accessing enables you to download data that you have found or requested, either directly or through a link or a portal. Reusing involves integrating data that you have accessed or downloaded for your own research or a new purpose. You can also use metadata to understand and interpret the data, such as its meaning, context, and quality. Finally, you can cite and acknowledge the data that you have reused or integrated in your publications, presentations, or reports. Metadata can also generate a citation or reference for the data following the format and style of your field or discipline.