Fazliev A.Z . , Kozodoev A.V., Privezetsev A.I.
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Transcript of Fazliev A.Z . , Kozodoev A.V., Privezetsev A.I.
Fazliev A.ZFazliev A.Z.., Kozodoev A.V., Privezetsev A.I., Kozodoev A.V., Privezetsev A.I. Institute of Atmospheric Optics SB RAS, Tomsk, RussiaInstitute of Atmospheric Optics SB RAS, Tomsk, Russia
Annotating theAnnotating the Information Resources Information Resources in the Distributed Information System in the Distributed Information System
on Molecular Spectroscopyon Molecular Spectroscopy
Annotating theAnnotating the Information Resources Information Resources in the Distributed Information System in the Distributed Information System
on Molecular Spectroscopyon Molecular Spectroscopy
The author would like to acknowledge the Russian Foundation for Basic Research for financial support
(grant 05-07- 90196)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The subject of atmospheric spectroscopyThe subject of atmospheric spectroscopy: : Molecule structure parametersMolecule structure parameters ((energy levelsenergy levels, , intermolecular potential intermolecular potential parametersparameters,…),…)Molecula spectraMolecula spectra ( (vibrationalvibrational, , rotationalrotational, , vibration-rotationalvibration-rotational) ) Spectral functionsSpectral functions ( (absorption coefficientabsorption coefficient, , transmittance functiontransmittance function, , absorption absorption cross-sectioncross-section, … ), … )
MMethodethodss of testing: of testing: experimental measurementsexperimental measurements, , quantum mechanical and quantum mechanical and semiempirical calculationssemiempirical calculations
Data levelData level:: 50 molecules are of interest for atmospheric research. Complete 50 molecules are of interest for atmospheric research. Complete data for the water molecule reflected in data for the water molecule reflected in 300 000 000 300 000 000 spectral linesspectral lines (99,5% - (99,5% - weak linesweak lines).).
Spectral data description levelSpectral data description level:: some line parameters are described by some line parameters are described by uuncertainty indices and bibliographyand bibliography. .
IntroductionIntroductionIntroductionIntroduction
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
HistoryHistory HistoryHistory
USA. Works are carried on from the late sixties. The databank HITRAN is created.
France. Works are carried on from the mid-seventies. The databank GEISA is created.
Russia. Works on informational resources for molecular spectroscopy are carried on from early eighties at the Institute of Atmospheric Optics SB RAS. The early nineties initiated the client side information systems. The advent of Internet technologies allowed development of a new type of information systems for the domain of molecular spectroscopy. The information resource (http://spectra.iao.ru) is based on the databanks Hitran and Geisa.
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Molecular spectroscopy web sitesMolecular spectroscopy web sites
((BabikovBabikov YuYu..LL., ., Golovko V.FGolovko V.F., ., Mikhailenko S.NMikhailenko S.N.) (1999-2004).) (1999-2004)
Molecular spectroscopy web sitesMolecular spectroscopy web sites
((BabikovBabikov YuYu..LL., ., Golovko V.FGolovko V.F., ., Mikhailenko S.NMikhailenko S.N.) (1999-2004).) (1999-2004)
Spectroscopy of Atmospheric Gases http://spectra.iao.ru
Carbon Dioxide Spectroscopic Databank (http://cdsd.iao.ru)
Spectroscopy & molecular properties of Ozone (http://ozone.iao.ru)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Problems solved within these web sitesProblems solved within these web sitesProblems solved within these web sitesProblems solved within these web sites
1. 1. Spectroscopy of Atmospheric GasesSpectroscopy of Atmospheric Gases • Survey of the content of various datasources: HITRAN and GEISA spectral databanks, original
data obtained by IAO researchers in collaboration with other scientists, H2O spectra simulated by Partridge and Shwenke etc...
• Simulation of intensity diagram, absorption coefficient profile, transmittance, absorption, and radiance spectra at given conditions for selected molecule, isotopic species, and set of spectral bands or for selected wavenumber region and gas mixture.
• Spectra convolution with a given apparatus function. • Direct problem solution (spectrum simulation by given hamiltonian and dipole moment
parameters). • Gas and/or isotopic species mixture preparation by user. • Uploading of user spectra to server side and comparison of them to spectra obtained with the
system.
2. 2. Spectroscopy & Molecular Properties of OzoneSpectroscopy & Molecular Properties of Ozone • molecular structure and spectroscopic constants in the ground electronic state • potential function, dipole moment surface, transition moments • vibration and vibration-rotation energies and wavefunctions, isotopic effects • simulated and experimental spectra from MW to Infrared • Gas and/or isotopic species mixture preparation by user. • Uploading of user spectra to sever side and comparison of them to spectra obtained with the
system.
3. 3. Carbon Dioxide Spectroscopic DatabankCarbon Dioxide Spectroscopic Databank • Survey of the content of CDSD, HITRAN/HITEMP, GEISA spectral databanks for CO2 molecule
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
IntroductionIntroductionIntroductionIntroduction
TechnologyTechnology
Organization
DB
Rough data
Public Public DBDB
Multimedia(video, sound, animation)
Metadata
e-Science
CalculationsCalculations
ExperimentExperiment
Information Resources of
e-Science
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
David De Roure, Nicholas Jennings, Nigel Shadbolt, A Future e-Science
Infrastructure, Report for EPSRC/DTI Core e-Science Programme, 2001.
IntroductionIntroductionIntroductionIntroduction
The Data-Computation LayerThe Data-Computation Layer
The Information LayerThe Information Layer
The Knowledge The Knowledge LayerLayer
e-Science
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
System level
Middleware level
Application and interfaces level
Data and computation
Interface human-PC Interface PC-PC
Operating system, compilers
Database Management System
Hardware
Web server
Soft
ware Metadata service
Authorization, applied logic, linguistic support, dialog system facility, etc
Middleware core
IntroductionIntroductionPortal ATMOS. MiddlewarePortal ATMOS. Middleware
IntroductionIntroductionPortal ATMOS. MiddlewarePortal ATMOS. Middleware
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The problems of molecular spectroscopyThe problems of molecular spectroscopyThe problems of molecular spectroscopyThe problems of molecular spectroscopy
Isolated molecule structureProblems: Finding of Watson’s Hamiltonian constants, parameters of short and long range
potential, wave functions and energy levels
Molecular spectral propertiesProblems: Finding of spectral line parameters (wave number, intensity, line width, line shift,
…). Identification of spectral lines from experimental spectra.
Spectral properties of atmospheric gasesProblems: Weak line study Continuum problem
Web site “Atmospheric spectroscopy” (http://saga.atmos.iao.ru)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Tomsk (IAO SB RAS)
Moscow
St.Petersburg
N.Novgorod
Data and metadata exchangeBasic host of DIS
Tomsk (TSU)
Metadata exchange
Client host
?
?
Distributed IS oriented for the problems of Distributed IS oriented for the problems of molecular spectroscopy (RFBR project)molecular spectroscopy (RFBR project)
Distributed IS oriented for the problems of Distributed IS oriented for the problems of molecular spectroscopy (RFBR project)molecular spectroscopy (RFBR project)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The Data-Computation LayerThe Data-Computation Layer The Data-Computation LayerThe Data-Computation Layer
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Data groups in the distributed ICS Data groups in the distributed ICS ““Molecular spectroscopyMolecular spectroscopy""
1. Basic parameters of a molecule
These are the characteristics that determine molecular energy. Depending of description method they can be either full molecular Hamiltonian parameters (potential energy, dipole moment, etc.) or effective Hamiltonian parameters (rotational, centrifugal, and resonance constants, effective dipole moment parameters, etc.). Can add quadruple, octupole molecular moments and other parameters characterizing intermolecular interaction in gases.
2. Spectral line parameters- Parameters of isolated spectral line,- “Local” and “global” quanta indexes,- Collision dependent parameters.
3. Spectral functionsAbsorption coefficient, transmittance function, absorption cross-section, etc.
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Absorption coefficient. Data structureAbsorption coefficient. Data structureAbsorption coefficient. Data structureAbsorption coefficient. Data structure
ExperimentSubstance Absorbing gas. Buffer gas.Thermodynamic conditions Temperature. Pressure. Partial pressure of buffer gas.Spectral parametersResolution. Path length. Frequency range.Absorption coefficientTransition frequency. Absorption coefficient.
CalculationSubstance Absorbing gas. Buffer gas.Thermodynamic conditions Temperature. Pressure. Partial pressure of buffer gas.Spectral parametersFrequency range. Contour type.Absorption coefficientTransition frequency. Absorption coefficient.
Data source Spectral line parameters. Statistical sums.
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Basic concepts Basic concepts Basic concepts Basic concepts
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Parameters of spectral linesParameters of spectral lines ((entityentity))
Isolated molecule- Vacuum wavenumber- Intensity- Lower level energy- Statistical weight of lower level- Identification
Interacting molecule (gas)- Line shift- Pressure induced linewidth (selfbroadening, buffer molecule
broadening)- Temperature dependence of linewidth
Other parameters- Reference indices- Uncertainty indices
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The origin of transition frequency and intensity- experiment- calculation- synthetic
Intensity value scale- absolute- relative
Uncertainty - relative error- absolute error
Parameters of spectral linesParameters of spectral lines ((attributesattributes))
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Last version ofLast version of metadatametadataLast version ofLast version of metadatametadata
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Data source
Intensity
Low Energy Level
Transition frequency Origin
Upper and lower statistical weight
Error Type
Identification
Spectral line parameters of isolated molecule
Error TypeOrigin Value
Pressure Shift
Temperature Dependence (on Width)
Collisional Width Origin Error Type
Spectral line parameters of interactive molecule
Error TypeOrigin
Buffer Gas Ne, He, Ar, O2, H2, H2O, CO2, air, self, …
Spectral Line Parameters InputSpectral Line Parameters InputSpectral Line Parameters InputSpectral Line Parameters Input
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Spectral Line Parameters InputSpectral Line Parameters InputSpectral Line Parameters InputSpectral Line Parameters Input
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The process of input of the user data on spectral line parameters is based on substance classification and on the list of spectral line parameters. The general input processes are illustrated in Fig. 1.The data input process consists of several steps, where the user describes his data. This description supposes some standard metadata that refers to the resources and thermodynamic conditions the data is associated with. The user forms the structure to input the data and specifies the values for his selected attributes.
1. Watson’s Hamiltonian constants2. Energy levels and wave functions 3. Long range part of intermolecular potential (dipol, quadrupole, …, octopole
moments).4. Short range part of intermolecular potential (for example, Lennard-
Jones potential, - depth of potential well, σ - range of repulsive force)
Molecular structure dataMolecular structure dataMolecular structure dataMolecular structure data
Molecule classification:Class for Molecule (Linear triatomic molecules with large Fermi resonance , Non-linear triatomic molecules, Diatomic molecules, … )
Symmetry Group (C2v, Td, Cinf v, ... ) Group Classification (Asymmetric rotor, Spherical rotor, Doublet- П ground electronic states (half-integer J , integer F), … )
Data source Basic physical quantities
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
XML NotationXML NotationXML NotationXML NotationXML-SchemeXML-Scheme RDFRDF--SchemeScheme
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Data entryData entry
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Substance choiceSetting of thermodynamic and spectral parametersData source choice Setting of approximations for calculations
Absorption coefficient calculationAbsorption coefficient calculation
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Absorption coefficient metadataAbsorption coefficient metadata
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Data and metadata for machine processingData and metadata for machine processing
XML-document
RDF-documentDC-metadata
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Web LanguagesWeb Languages Existing Web languages extended to facilitate content descriptionExisting Web languages extended to facilitate content description
• XMLXML XML Schema ( XML Schema (XMLSXMLS))• RDFRDF RDF Schema ( RDF Schema (RDFSRDFS))
XMLSXMLS is is notnot an ontology language an ontology language
RDFSRDFS isis recognisable as an ontology language recognisable as an ontology language
• ClassesClasses and and propertiesproperties• Sub/super-classesSub/super-classes (and properties) (and properties)• RangeRange and and domaindomain (of properties) (of properties)
OWLOWL is an ontology vocabulary is an ontology vocabulary• Well defined Well defined semanticssemantics• Formal propertiesFormal properties well understood (complexity, decidability) well understood (complexity, decidability)• Known Known reasoning algorithmsreasoning algorithms• Implemented systemsImplemented systems (highly optimised) (highly optimised)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The Information LayerThe Information Layer The Information LayerThe Information Layer
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Metadata description methodsMetadata description methods
Register formationRegister formationCDF, RSS, AtomCDF, RSS, Atom
Formatted metadataFormatted metadata RDFRDF RequiredRequired - - DCDC Dependent on resource typeDependent on resource type
CIMI, MARCCIMI, MARC
Domain metadata RDFDomain metadata RDF based onbased on RDF-schemeRDF-scheme andand OWLOWL
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Compound data sourcesCompound data sources
+
=
Tr.Freq. Line Intensity |R|2 Air HW Self HW T-depend. Pres. shift MoleculeIdentification
H2O00.2752 2.401e-30 3.48e-1 0.034 0 {v1v2v3 j ka kc}0.04
Data source 1
Tr.Freq. Line Intensity |R|2 Air HW Self HW T-depend. Pres. shift MoleculeIdentification
H2O0.2752 2.401e-30 0.041 0.0030 0 0.0035
Data source 2
Tr.Freq. Line Intensity |R|2 Air HW Self HW T-depend. Pres. shift MoleculeIdentification
H2O0.0030.2752 2.401e-30 3.48e-1 0.041 0.035 {v1v2v3 j kakc}0.04
DS 1=DS 2 DS 1=ds 2 DS 1 DS 2 DS 2 DS 1 DS 2 DS1=DS 2DS 1
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Comparison of calculated absorption Comparison of calculated absorption coefficient of COcoefficient of CO22 with experimental values with experimental values
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
СО2-CO2
15 mkm Т=296 К Contour of Moskalenko 4.3 mkm Т=296 К 2397 - 2575 сm-1 Contour of Benedict
Т=296 К 2380 - 2585 cm-1 Contour of Boulet
Т=296 К 2400 - 2580 cm-1 Contour of Gal’tsev
Т=296 К 2140 - 2250 cm-1 Contour of Boulet, asymmetric
Т=296 К Contour of Moscalenko Т=218 К 2380 - 2585 cm-1 Contour of Boulet
Т=190-800 К 2400 - 2600 cm-1 Contour of Hartman 2.7 mkm Т=296 К 3750 – 4100 cm-1 Contour of Gal’tsev Т=296 К 3750 – 4100 cm-1 Contour of Bezard Т=296 К Contour of Moscalenko 2.3 mkm
Т=296 К 3800 – 4700 cm-1 Contour of Tonkov 2.0 mkm
Т=296 К Contour of Moscalenko 1.6 mkm
Т=296 К Contour of Moscalenko 1.4 mkm
Т=296 К 6985 – 7100 cm-1 Contour of Gal’tsev
Т=296 К Contour of Moscalenko
Absorption coefficientAbsorption coefficient. . What elseWhat else??
Line contour• Typical (Voigt, Doppler, Lorentz)
• Line wing theory (Tvorogov) (CO2, Н2О)
• Empirical contours СО2-CO2, Н2О-Н2О СО2-N2, СО2-O2, Н2О-Н2О + Н2О-N2
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Problems with RDFSProblems with RDFS RDFS is RDFS is too weaktoo weak to describe resources in sufficient detail to describe resources in sufficient detail
• No No localised range and domainlocalised range and domain constraints constraints Can’t say that the range of Can’t say that the range of isDissociatedisDissociated is molecules is molecules
when applied to moleculeswhen applied to molecules• No No existence/cardinalityexistence/cardinality constraints constraints
Can’t say that all Can’t say that all triatomic moleculetriatomic moleculess have exactly 3 have exactly 3 atomsatoms
• No No transitive, inverse or symmetricaltransitive, inverse or symmetrical properties properties Can’t say that Can’t say that isPartOfisPartOf is a transitive property, that is a transitive property, that
hasPart is the inverse of hasPart is the inverse of isPartOfisPartOf or that or that come_into_collission_withcome_into_collission_with is symmetrical is symmetrical
• …… Difficult to provide Difficult to provide reasoning supportreasoning support
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
The Knowledge LayerThe Knowledge LayerThe Knowledge LayerThe 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.”
David De Roure, Nicholas Jennings, Nigel Shadbolt, A Future e-Science Infrastructure, Report for EPSRC/DTI Core e-Science Programme, 2001.
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Ontologies and Ontology RepresentationsOntologies and Ontology Representations
Most of the time we will just say “concept” and Most of the time we will just say “concept” and “ontology” but whenever anybody starts “ontology” but whenever anybody starts getting religious, remember…getting religious, remember…• It is only a representation!It is only a representation!
We are doing engineering, not philosophy – although We are doing engineering, not philosophy – although philosophy is an important guidephilosophy is an important guide
There is no one way!There is no one way!• But there are consequences to different waysBut there are consequences to different ways
and there are wrong waysand there are wrong ways• and better or worse ways for a given purposesand better or worse ways for a given purposes
• The test of an engineering artefact is whether it is fit The test of an engineering artefact is whether it is fit for purposefor purpose
Ontology representations are engineering artefactsOntology representations are engineering artefacts
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Clash of intuitionsClash of intuitions• Subject Matter Experts motivated by custom & practiceSubject Matter Experts motivated by custom & practice
Prototypes & GeneralitiesPrototypes & Generalities• Logicians motivated by logic & computational tractability Logicians motivated by logic & computational tractability
Definitions and UniversalsDefinitions and Universals Transparency & predictability vs Transparency & predictability vs
Rigour & CompletenessRigour & Completeness
Conflation of ModelsConflation of Models• Meaning: Correctness of Classification & retrievalMeaning: Correctness of Classification & retrieval• Retrieval: Task of discovery, search, or findingRetrieval: Task of discovery, search, or finding• Use: Task of data entry, decision support, …Use: Task of data entry, decision support, …• Acquisition: Task of capturing knowledgeAcquisition: Task of capturing knowledge• Quality assurance: Criteria for whether it is ‘correct’Quality assurance: Criteria for whether it is ‘correct’
Why ontology is hardWhy ontology is hard
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Special features of the ontology for Special features of the ontology for molecular spectroscopymolecular spectroscopy
Special features of the ontology for Special features of the ontology for molecular spectroscopymolecular spectroscopy
Presentation levelsPresentation levels::Physical modelPhysical model – – Mathematical modelMathematical model – – Information modelInformation model – – Program modelProgram model - …. - ….
Data Computation
Top- and bottom-level domain ontologiesTop- and bottom-level domain ontologies:: Quantum mechanics and electrodynamics (top level)Molecular spectroscopy Mathematical algorithms (bottom level)
Resource description in spectroscopyResource description in spectroscopy – – OWL DLOWL DL
Data sources:Experiment and calculation
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Top-Level Categories (John Sowa)Top-Level Categories (John Sowa)http://www.jfsowa.com/ontology/toplevel.htmhttp://www.jfsowa.com/ontology/toplevel.htm
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Thank you for your attentionThank you for your attention
The authors would like to acknowledge the experts in the domain of molecule spectroscopy
corresponding member of RAScorresponding member of RAS S.DS.D. . Tvorogov Tvorogov ProfProf. . A.D. Bykov (IAO SB RAS, Tomsk)A.D. Bykov (IAO SB RAS, Tomsk)
ProfProf. . O.B. Rodimova (IAO SB RAS, Tomsk) O.B. Rodimova (IAO SB RAS, Tomsk) Prof. N.N.Fillipov (SPbU, S.Petersburg) Prof. N.N.Fillipov (SPbU, S.Petersburg) Prof. M.V.Tonkov (SPbU, S.Petersburg)Prof. M.V.Tonkov (SPbU, S.Petersburg)
Prof. J.Tennyson (UCL, London)Prof. J.Tennyson (UCL, London)Dr. M.Yu.Tret’yakov (IAP RAS, N.Novgorod)Dr. M.Yu.Tret’yakov (IAP RAS, N.Novgorod)Dr. O.V. Naumenko (IAO SB RAS, Tomsk)Dr. O.V. Naumenko (IAO SB RAS, Tomsk)
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005
Digital Libraries: Advanced Methods and Technologies. Digital Collections. Seventh National Russian Research Conference, Yaroslavl, October 04 - 06, 2005