Promises and Perils of Big Data—Philosophical Constraints on Chemical Ontologies

Materials research is experiencing a paradigm shift in the way it interacts with data. So-called “big data” is collected and used at unprecedented scales with the idea that algorithms can be designed to aid in chemical discovery. As data-enabled practices become ever more ubiquitous, researchers must consider the organization and curation of their data, especially as it is presented both to humans and increasingly intelligent algorithms. One of the most promising organizational schemes for big data is an ontology, a system for representing relations among objects and properties in a domain of discourse. The future of materials research will be shaped by the choices made in developing big data chemical ontologies. How such ontologies will work should, therefore, be a subject of significant attention in the chemical community. We recommend answering these questions with an interdisciplinary approach that draws on the long history of philosophers of science asking questions about the organization of scientific concepts, constructs, models, and theories. We present insights from these long-standing studies and initiate new conversations between chemists and philosophers. We illustrate how the “blooming, buzzing confusion” of chemical ontologies is merely a feature of advanced chemical thought, and an often desirable one at that. Ultimately, we advocate for a shift in time and energy away from a quest for a universal chemical ontology and towards developing context-sensitive pluralistic ontologies in collaboration with philosophers.