Throughout your research one should be collecting documentation about your experiment and about the contents of your research files/data. As a result, research documentation can be divided into two types of information – one being experimental information like those contained in laboratory notebooks and two, being metadata or information about the data like README.txt files about your research data files.
Laboratory notebooks, which can be either electronic or print, are an essential way and primary record of tracking and accurately recording your research results and process. Consistency and descriptiveness of your research notes about your research methods, hypotheses, analysis, results, calculations, and statistical methods will increase the integrity and validity of your research especially when one wants to reproduce your experiment or share research at a later date.
Lab Notebook Features:
Some important information that you might want to capture in your lab notebooks include the following:
Metadata is information about data; the existence of metadata, whether structured or unstructured, is essential for data to be understood, interpreted, and used.
Metadata documentation may physically manifest itself in the following forms:
Metadata documents data at two levels – research project level and dataset level.
In order to increase the long term discovery, preservation, and understanding of your data at a later date, it is wise to structure your metadata.
In order to standardize the language to describe your documentation/metadata in order to increase the dataset’s discovery, you might want to use ontologies/controlled vocabularies to describe your data. Ontologies are shared vocabularies that describe certain aspects/relationships with a respective discipline. Through using ontologies/controlled vocabularies, you are increasing the user comprehension of your dataset. The following list, though not exhaustive, are some popular biomedical ontologies: