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Expressing Measurements and Chemical Systems for Physical Property Data Peter Linstrom National Institute of Standards and Technology Gaithersburg, MD, USA Outline Nature of physical property data Historical record or interpretation


  1. Expressing Measurements and Chemical Systems for Physical Property Data Peter Linstrom National Institute of Standards and Technology Gaithersburg, MD, USA

  2. Outline • Nature of physical property data • Historical record or interpretation • Limitations of automated systems • Problem areas • Summary CODATA 2002 Conference October 3, 2002 2

  3. Physical Property Data • A numeric tuple which applies to a physical system • Describing how the numeric value was obtained from the system is difficult – Identification of techniques, equipment, ancillary data used in calculations and calibrations. CODATA 2002 Conference October 3, 2002 3

  4. Physical Property Data • Describing the system is difficult – Identification of sample: chemical species and concentrations • Recording the numeric tuple is easy CODATA 2002 Conference October 3, 2002 4

  5. Historical Record or Interpretation Two goals (non-exclusive) goals: 1.) Historical record – What was measured, computed, or estimated? – How was this done? 2.) Basic knowledge – What do we know about this property? – What is the probable range of the numeric value? CODATA 2002 Conference October 3, 2002 5

  6. Historical Record or Interpretation • Historical record – Does not change – Applies to specific physical systems and measurements • Basic knowledge – Built on analysis of the historical record – Applies to an “idealized” physical system – Improves through scientific processes CODATA 2002 Conference October 3, 2002 6

  7. Example • 1998 Roux et al, Fraday Trans. • Stability of dimethyl benzenedicarboxolates COOMe COOMe COOMe COOMe COOMe COOMe CODATA 2002 Conference October 3, 2002 7

  8. Example 2 C 6 H 5 CO 2 Me → C 6 H 4 (CO 2 Me) + C 6 H 6 Endothermicity of gas phase reaction: ortho 52.3 kJ/mol meta 29.2 kJ/mol para 30.4 kJ/mol Quite different from dinitro and dicyano benzenes CODATA 2002 Conference October 3, 2002 8

  9. Example • 2002 Roux et al, Phys. Chem. Chem. Phys. • ∆ f Hº methyl benzoate gas (kJ/mol): 1971 Hall et al -299.8 1980 Guthrie et al -269.3 ± 5.1 1994 Pedley -287.9 ± 2.4 1998 Maksimuk et al -277.74 ± 1.2 2002 Roux et al -276.1 ± 4.0 CODATA 2002 Conference October 3, 2002 9

  10. Example 2 C 6 H 5 CO 2 Me → C 6 H 4 (CO 2 Me) + C 6 H 6 Revised endothermicity of gas phase reaction: ortho 28.7 kJ/mol meta 5.6 kJ/mol para 6.8 kJ/mol Similar to dinitro and dicyano benzenes CODATA 2002 Conference October 3, 2002 10

  11. Automated Systems • Automated systems require data with well defined semantics • Portions of physical property data are recorded in natural language (literature) • Need procedures to map information to a form appropriate for automated systems CODATA 2002 Conference October 3, 2002 11

  12. Automated Systems • Mapping of information to computer friendly semantics may involve – Loss of information – A judgement on the part of the archivist (introduction of information not explicitly contained in the original source) – Blurring of the line between historical record and interpretation CODATA 2002 Conference October 3, 2002 12

  13. Automated Systems • Some options for expressing information – Develop taxonomy of codes – Token value pairs – Incorporate into database design – Text comments (loss of data processing capability) – Ignore the information CODATA 2002 Conference October 3, 2002 13

  14. Automated Systems Increasing complexity Token / Value Language Pairs Simple Complex Taxonomies Taxonomies Increasing assumptions, judgements CODATA 2002 Conference October 3, 2002 14

  15. Automated Systems • Proper design of systems for expressing data requires significant domain knowledge – Definition of appropriate taxonomies, codes, etc. – Knowledge of what will be important to future investigators – Knowledge of what can be safely ignored CODATA 2002 Conference October 3, 2002 15

  16. Some Problem Areas • Chemical identification • Taxonomies for methods • Describing domain-specific meta-data CODATA 2002 Conference October 3, 2002 16

  17. Chemical Identification • Identification of pure species can be difficult • Identification of mixtures is a superset of the problem for single species • Chemical nomenclature is too complex for most data systems to handle CODATA 2002 Conference October 3, 2002 17

  18. Chemical Identification • Registry of species – Simplifies identification to an integer number – Maintained by third parties – Species may not be in registry – Identification may not be precise (isomers) – Deprecated entries – Users consult secondary sources – errors propagate CODATA 2002 Conference October 3, 2002 18

  19. Chemical Identification • Chemical structure – No third party – Less ambiguity, but more complex semantics – Expensive to draw or look up – Costs decreasing with modern technology CODATA 2002 Conference October 3, 2002 19

  20. Chemical Identification • Purity / uncertainty of composition – May not be known – Purification / synthesis technique may be provided – Often omitted from database CODATA 2002 Conference October 3, 2002 20

  21. Taxonomies for Methods • Classification of the manner in which a value was obtained • Instrument type, model form natural divisions – Appropriate resolution determined by archivist • How does one handle unique methods? – Science is not static – taxonomies will grow CODATA 2002 Conference October 3, 2002 21

  22. Taxonomies for Methods • Lias, et al, Ionization Potential Database – Compiled over many years – Taxonomy for basic measurement types – Additional codes added to supplement supplement taxonomy for new methods which cross existing hierarchical boundaries (e.g. electron impact and laser spectroscopy) CODATA 2002 Conference October 3, 2002 22

  23. Domain Specific Meta-Data • Meta-data recognized by archivist (domain specialist) as significant • Need method to encode in computer friendly format – Taxonomies – Token value pairs CODATA 2002 Conference October 3, 2002 23

  24. Domain Specific Meta-Data • Affefy, Liebman, and Stein – Neutral Thermochemistry Archive – Meta-data options expanded as archive grew – Correction to current CODATA heats of formation: done, not-done, or not-possible – Data disagrees with previously published data: acknowledged by author(s), or not acknowledged CODATA 2002 Conference October 3, 2002 24

  25. Summary • Two pairs of trade-offs – Historical record vs. interpretation – Semantic complexity vs. loss of information • Important for archivists and researchers to be aware of the compromises that are made CODATA 2002 Conference October 3, 2002 25

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