Finding the data that is most relevant to a given context is a major obstacle to reusing and integrating existing data. The scientific literature that provides descriptions of the experiments that led to the data is the primary source of metadata. We manually annotated 100 recent open access publications in Analytical Chemistry as semantic graphs to encourage the development of natural language processing techniques for extracting this data from articles. Because we are particularly interested in the subject, which also falls under the purview of a number of ontologies and controlled vocabularies, we concentrated our efforts on articles that included a mention of mass spectrometry in their experimental sections. The resulting gold standard dataset is accessible to the general public and can be used to verify automated methods for locating this metadata in the literature. We also made a few observations regarding the experiment structure, description, and open access publication in this journal.
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