RDA and Chemistry

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23 January 2017 21157 reads

Chemical research data is fundamentally the most important product that chemists create as it guides future research and allows us to understand how chemistry works, what we can do with it and how it affects our lives. Chemistry, as a discipline, has long focused on its own specific needs in analyzing and communicating chemical data, especially the representation and identification of chemical structures. Today’s chemical informaticians (cheminformaticians) have pushed technology to make storing and searching chemical information easier and more standardized for increasing amounts of data.

The time has come, however, to take a step back and look at chemical informatics as it relates to the needs relative to: dealing with large amounts of heterogeneous data that are stored in different ways, how we transmit chemical information to the many other disciplines that need it, and how we semantically represent it in digital form. Looking to efforts of other disciplines and understanding and appreciating the importance and impact of generalized data technologies and RDA outcomes will strengthen chemistry and help move it toward open data in a way that is interoperable and forward thinking.

The Chemistry Research Data Interest Group (CRDIG) is focused on mechanisms by which we can improve chemical informatics and highlight its importance in the global data economy, specifically:

  • Bringing together important stakeholders relative to open chemical data (e.g., the American Chemical Society - Division of Chemical Information, the International Union of Pure and Applied Chemistry (IUPAC), and others)
  • Bridging the chemical informatics and RDA communities to help appreciate and understand what each has to offer
  • Development of both RDA Working Group and IUPAC project proposals for important domain activities such as:
    • Establishing new or revised metadata, ontology, chemical structure, or data format standards
    • Characterization of the different chemical information types, identification of the critical points in the data life-cycle, and mapping of gaps in interoperability