A.Z. Fazliev, N.A.Lavrentiev, A.I.Privezentsev V.E. Zuev Institute of Atmospheric Optics SB RAS, Academician Zuev Square 1, Tomsk , Russia HITRAN Conference, Cambridge, June 2010

Introduction e-Science. Service oriented architecture e-Science. Three layers information systems The Data, Information and Knowledge Lifecycle Architecture of Model of Quantitative Molecular Spectroscopy Data Validity Formal constraints Selection rules. Primary data sources Publication constraints Non-formal constraints Current State of HITRAN Conference, Cambridge, June 2010

e-Science. Service oriented architecture De Roure D., Jennings N., Shadbolt N. A Future e-Science Infrastructure // Report commissioned for EPSRC/DTI Core e-Science Programme p. HITRAN Conference, Cambridge, June 2010

e-Science. Three layers information systems De Roure D., Jennings N., Shadbolt N. A Future e-Science Infrastructure // Report commissioned for EPSRC/DTI Core e-Science Programme p. The Data-Computation Layer “As soon as computers are interconnected and communicating we have a distributed system, and the issues in designing, building and deploying distributed computer systems have now been explored over many years. First it positions the Grid within the bigger picture of distributed computing, asking whether it is subsumed by current solutions. Then we look in more detail at the requirements and currently deployed technologies in order to identify issues for the next generation of the infrastructure. Since much of the grid computing development has addressed the data-computation layer, this section particularly draws upon the work of that community.” The Information Layer “This layer is focus firstly on the Web. The Web’s information handling capabilities are clearly an important component of the e-Science infrastructure, and the web infrastructure is itself of interest as an example of a distributed system that has achieved global deployment. The second aspect addressed is support for collaboration, something which is key to e- Science. The information layer aspects build on the idea of a ‘collaboratory’, defined as a “centre without walls, in which the nation’s researchers can perform their research without regard to geographical location - interacting with colleagues, accessing instrumentation, sharing data and computational resource, and accessing information in digital libraries.” The Knowledge Layer “The aim of the knowledge layer is to act as an infrastructure to support the management and application of scientific knowledge to achieve particular types of goal and objective. In order to achieve this, it builds upon the services offered by the data-computation and information layers. The first thing to reiterate at this layer is the problem of the sheer scale of content we are dealing with. We recognise that the amount of data that the data grid is managing will be huge. By the time that data is equipped with meaning and turned into information we can expect order of magnitude reductions in the amount. However the amount of information remaining will certainly be enough to present us with a problem – a problem recognised as infosmog – the condition of having too much information to be able to take effective action or apply it in an appropriate fashion to a specific problem. Once information is delivered that is destined for a particular purpose, we are in the realm of the knowledge grid that is fundamentally concerned with abstracted and annotated content, with the management of scientific knowledge.” HITRAN Conference, Cambridge, June 2010

The Data, Information and Knowledge Lifecycle De Roure D., Jennings N., Shadbolt N. A Future e-Science Infrastructure // Report commissioned for EPSRC/DTI Core e-Science Programme p. Acquire Modelling Retrieve Publish Maintain The challenge of knowledge publishing or disseminating can be described as getting the right data, information and knowledge, in the right form, to the right person or system, at the right time …. HITRAN Conference, Cambridge, June 2010

What is the hierarchy of the problems ? 1.Lifecycle. Implement Distributed Information System that allows simplify for the investigator aquire, retrieve and publish data and information 2.Publish. Create Publishing Tools 3.Key question. Guarantee Data Validity 4.Constraints Types. 1. Restrictions on physical entity values (for instance, selection rules). Verification of the restrictions is identical to verification of statement 2. Existence (Publication) Restrictions ( ) Getting the right data, ….. - existential quantifier- universal quantifier S – spectroscopy domain, X- physical entity characterized by quantum numbers, Y – published data set HITRAN Conference, Cambridge, June 2010

Web-service of publications data base synchronization Web-service for the formation of a homogeneous set of inverse and direct tasks solutions properties in a distributed system Web-service for the formation of an ontology of molecular spectroscopy tasks’ solutions properties Interfaces Protégé interface Data - computation layer Information layer Knowledge layer System of direct and inverse spectroscopy problems’ solutions input Spectral functions calculation Formation of composite problems’ solutions Inference engine Logical consistency check Decomposition of problems’ solutions according to publications Description of non-calculable properties of molecular spectroscopy inverse and direct problems’ solutions Computation of calculated properties of direct and inverse spectroscopy problems’ solutions Composite solutions of spectroscopy tasks Primary solutions of inverse spectroscopy tasks Primary solutions of direct spectroscopy tasks Publications DB Ontology of spectroscopy tasks’ solutions properties Molecular spectroscopy tasks’ solutions properties Data Node Applications InterfacesWeb-services Node Architecture of Semantic Web approach HITRAN Conference, Cambridge, June 2010

Model of Quantitative Molecular Spectroscopy Isolated molecules spectral line parameters (T2) Isolated molecule physical characteristics (T1) Spectral line profile parameters (T3) Spectral functions calculation (T4) Direct Problems Inverse Problems Computations Measurements Two chains of problems are selected for domain Isolated molecule energy levels (T7) Einstein coefficients (T6) Interacting molecule spectral line parameters (ET) Spectral functions measurement (E) Quantum numbers assignment to spectral lines (T5)

Elementary solution of spectroscopic problem Elementary source characteristics Elementary source characteristics molecule – H 2 O the list of physical quantities – energy levels E (cm -1 ), Quantum numbers (v 1 v 2 v 3 J K a K c ), ……. publication - Schwenke D.W., New H 2 O Rovibrational Line Assignments. // Journal of Molecular Spectroscopy, 1998, v. 190, no. 2, p data - ……………………………………………………………… HITRAN Conference, Cambridge, June 2010 IUPAC Data group approach (information aspect)

Data Validity Formal constraints Data type – Quantum Numbers – natural numbers, … Intensity, Halfwidth, Frequency, Energy Levels – positive real numbers, …. Variation interval – 0 < wavenumbers < cm -1, cm/mol < intensity < cm/mol Selection rules - normal modes - k a +k c =J or J+1, ….. Publication constraint Whether data are published or not Other constraints (transitivity and antisymmetry axioms) ………………………………………….. Non-formal constraints Experts’ opinion XML OWL DL HITRAN Conference, Cambridge, June 2010

Selection rules. Primary data sources Problem Т1, Problem Т7Problem Т2, Problem Т6Problem Т3, Proble Т5 Direct Inverse H2OH2O 9(2), 30 (24) 5(0), 91 (47)5 (0), 183 (167) H 2 17 O 4(0), 19 (15) 5(1), 40 (31)4 (0), 19 (16) H 2 18 O 4(0), 18 (18) 5(1), 59 (35)4 (0), 29 (17) HDO 1(0), 32 (28) 3(0), 83 (56)2 (0), 8 (3) HD 17 O -, 3 (3) 2(0), 3 (3)2 (0), 6 (6) HD 18 O -, 5 (4) 2(0), 6 (6)2 (0), 7 (7) D2OD2O 1(1), 18 (8) 3(0), 38 (26)3 (0), 10 (7) D 2 17 O 1(0), 3 (3)2 (0), 1 (1) D 2 18 O 2(0), 6 (6)2 (0), 1 (1) 15(3), 125 (100) 28(2), 318 (207) 26(0), 264 (225) 9(2) Total number of data sources(Number of correct data sources) Privesentsev A.I., Ontological knowledge base implementation and software for information resources description in molecular spectroscopy, Tomsk State University, PhD Dissertation, 2009, 238 Pages HITRAN Conference, Cambridge, June 2010

Validity Publication constraints Informatics Restriction. RFC 2396: A (information) resource can be anything that has identity. Decomposition. Mathematical basis. Axiom of reflexivity: For each a, a=a. Physical constraint a st type of measurements --- > A1 a nd type of measurements -- > A2 Experimental accuracy Criteria of identity |A1 – A2| < The complete validated data set are published by IUPAC data group (J. Tennyson, P.F. Bernath, L.R. Brown, et al., IUPAC Critical Evaluation of the Rotational-Vibrational Spectra of Water Vapor. Part I. Energy Levels and Transition Wavenumbers for H 2 17 O and H 2 18 O, Journal of Quantitative Spectroscopy and Radiative Transfer, July 2009, V.110, no.9-10, P ) HITRAN Conference, Cambridge, June 2010

Decomposition. Hitran-2008 (H 2 18 O) H 2 18 O (N = 9753) (cm -1 ) Data source (inverse problem direct problem) Residual N= cm _StBe 1970_PoJo 2006_GoMaGuKn 1972_LuHeCoGo _ZoShOvPo 2007_ZoOvShPo 2007_ScPaTa_a 2007_ScPaTa_b 8 N= cm _GoMaGuKn 1972_LuHeCoGo 1987_BeKoPoTr 1999_MaNaNAOd 1976_FlGi 1981_Partridg _ZoShOvPo 2007_ZoOvShPo 2007_ScPaTa_a 2007_ScPaTa_b 0 N= cm _MaNaNAOd 1985_Johns 1981_Partridg 1976_FlGi _ScPaTa_a 2007_ScPaTa_b 2007_ZoOvShPo 2008_ZoShOvPo 0 N= cm _MaNaNAOd 1985_Johns 1980_KaKy 1978_KaKaKy 1977_Winther _ScPaTa_a 2007_ScPaTa_b 2008_ZoShOvPo 2007_ZoOvShPo 2 N= cm _Johns 1978_KaKaKy 1980_KaKy 1977_Winther 2003_MiTyMe 1998_Toth 1992_Toth 2006_LiDuSoWa 1983_Guelachv 1993_Toth 1971_WiNaJo 1978_JoMc 1975_ToMa 1994_Toth_a 1969_FrNaJo 1983_PiCoCaFl 1973_CaFlGuAm 1983_ToBr 2007_JeDaReTy 2002_MiTyStAl 1985_ChMaFlCa 1977_ToCaFl_a 1986_ChMaFlCa 1989_UlZhSh 2006_LiNaSoVo 1986_ChMaCaFl_b 2004_MaRoMiNa 1994_Toth_b 2007_MiLeKaCa 1977_ToFlCa_b 2001_MoSaGiCi 2001_MoSaGiCi 2005_ToTe 2006_LiHuCaMa 1987_ChMaFlCa 2005_ToNaZoSh _ScPaTa_a 2007_ScPaTa_b 2008_ZoShOvPo 2007_ZoOvShPo 1983_PiCoCaFl 302 N= cm _ChMaFlCa 2005_ToNaZoSh 2007_MaToCa 1995_ByNaPeSc 2002_TaBrTe 2005_TaNaBrTe _ZoOvShPo 2007_ScPaTa_a 2007_ScPaTa_b 2008_ZoShOvPo HITRAN Conference, Cambridge, June 2010

Publication constraints 0. L.S. Rothman, R.R. Gamache, A. Goldman, L.R. Brown, R.A. Toth, H.M. Pickett, R.L. Poynter, J.-M. Flaud, C. Camy-Peyret, A. Barbe, N. Husson, C.P. Rinsland, and M.A.H. Smith, “The HITRAN database: 1986 Edition,” Appl.Opt. 26, (1987) 26. H. Partridge and D.W. Schwenke, “The determination of an accurate isotope dependent potential energy surface for water from extensive ab initio calculations and experimental data,” J.Chem.Phys. 106, (1997). 28. J.P. Chevillard, J.-Y. Mandin, J.-M. Flaud, and C. Camy-Peyret, “H 2 18 O: line positions and intensities between 9500 and cm -1. The (041), (220), (121), (201), (102), and (003) interacting states,” Can.J.Phys. 65, (1987). 30. R.A. Toth, “Linelist of water vapor parameters from 500 to 8000 cm -1,” see Calculation from K.V. Jucks, private communication (2000). Composite data source Unpublished data source Published data and data in HITRAN are not the same HITRAN Conference, Cambridge, June 2010

J. Tennyson, P.F. Bernath, L.R. Brown, et al., IUPAC Critical Evaluation of the Rotational-Vibrational Spectra of Water Vapor. Part I. Energy Levels and Transition Wavenumbers for H 2 17 O and H 2 18 O Journal of Quantitative Spectroscopy and Radiative Transfer, July 2009, V.110, no.9-10, P J. Tennyson, P.F. Bernath, L.R. Brown, et al., IUPAC Critical Evaluation of the Rotational-Vibrational Spectra of Water Vapor. Part II. Energy Levels and Transition Wavenumbers for HDO, HD 17 O and HD 18 O Journal of Quantitative Spectroscopy and Radiative Transfer, Non-formal constraints HITRAN Conference, Cambridge, June 2010

Current State of the H 2 O H 2 S SO 2 CO 2 N 2 O NH 3 CH 4 C 2 H 2 CO O 2 OCS HNCO ~ 2000 articles H 2 O H 2 S CO 2 CO CH 4 ~ 1200 data sets e-Library (Primary Data) Digitized Data H 2 O H 2 S SO 2 O 3 N 2 O OCS NH 3 C 2 H 2 CO HBrO CO 2 CH 4 In the end of August 2010 CO 2 H 2 O H 2 S now + NH 3 CO CH 4 In the end of 2010 Upload Systems Data Base & Knowledge Base of DIS HITRAN Conference, Cambridge, June 2010

Summary ► A node prototype of a Distributed Information System for acquire, retrieve, publish and maintain data, information and knowledge in quantitative molecular spectroscopy is developed and implemented ► A component of the publishing tools provides formal validation of data is implemented ► IS – HITRAN Conference, Cambridge, June 2010

Acknowledgements We thank Prof. J.Tennyson for the assistance providing the creation of all data collections and Dr. S.Tashkun for his contribution in CO 2 data collection. Fazliev A. thanks Prof. Tyuterev Vl.G. for fruitful discussion on the publications constraints. This work has received partial support from RFBR and 7-th Framework Programme