Open AccessSemantic Annotation of Experimental Methods in Analytical Chemistry
Author(s) -
Magnus Palmblad,
Enahoro Asein,
Nina Bergman,
А. П. Иванова,
Lukas Ramasauskas,
Hazzar Mohammed Reyes,
Stefan Ruchti,
Leonardo Soto-Jácome,
Jonas Bergquist
Publication year - 2022
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.2c03565
Subject(s) - metadata , chemistry , information retrieval , context (archaeology) , computer science , annotation , process (computing) , controlled vocabulary , domain (mathematical analysis) , resource (disambiguation) , reuse , data science , world wide web , artificial intelligence , mathematical analysis , computer network , ecology , mathematics , biology , operating system , paleontology
A major obstacle for reusing and integrating existing data is finding the data that is most relevant in a given context. The primary metadata resource is the scientific literature describing the experiments that produced the data. To stimulate the development of natural language processing methods for extracting this information from articles, we have manually annotated 100 recent open access publications in Analytical Chemistry as semantic graphs. We focused on articles mentioning mass spectrometry in their experimental sections, as we are particularly interested in the topic, which is also within the domain of several ontologies and controlled vocabularies. The resulting gold standard dataset is publicly available and directly applicable to validating automated methods for retrieving this metadata from the literature. In the process, we also made a number of observations on the structure and description of experiments and open access publication in this journal.