SolutionsUseCase VirtualObservatory neutraltemperature 1a
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Plain Language Description
A user is interested in the characteristics of the Earth's neutral atmosphere above 100km in altitude, in particular the temperature as a function of time.
Search for and find a specific type of data in the CEDAR database and plot the data in a way that makes sense for the data type. At present a scientific user needs to know a lot about the types, locations and operating modes of instruments (also models and indices) to be able to locate, retrieve and use them.
This use-case will demonstrate how ontologies, and semantically-enabled interfaces can significantly reduce the level of detail that a person has to know about the data.
Describe a scenario of expected use
A user accesses a web interface offering selections to search for data that include the ability to search for instruments, date-time ranges and measured paramters.
The search mechanism must always return a non-null result, i.e. only valid choices are given to the user at each stage of the search.
Secure authentication is only enforced after data is found and accessed (i.e. not required for plotting the data).
Plotting output must be made available in the portal as well as in downloadable form.
Definition of Success
Location of relevant data for a suitable time period and visual display of that data as a time series, or two-dimensional representation (contours) for e.g. as a function of time and altitude (height) in the atmosphere.
Formal Use Case Description
Use Case Identification
- Use Case Designation
- Use Case Name
- Neutral Temperature time series.
The neutral temperature of the earth's neutral atmosphere can be recorded by a range of instruments. The Fabry-Perot Interferometer returns raw information that can be processed into a time series for neutral temperature.
- Prepared by:
- Luca Cinquini
- CISL/NCAR as part of the VSTO team
- August 1, 2005
- Version 1.2.a
- Modified by:
- August 1, 2005 Luca Cinquini - initial document
- August 3, 2005, Deborah McGuinness - mark up of language for initial document
- August 5, 2005, Peter Fox - conversion of format
- August 15, 2005, Peter Fox - update to format and content
- August 16, 2005, Luca Cinquini - updated Description section and added Process Model section, took first stub at VSTO tools section
- August 20-23, 2005, Peter Fox - clarified use-case description, added to vocabulary and VSTO ontology section, added references, preliminary classes (and instances) for instruments and classes for relevant parameters.
- August 25, 2005, Luca Cinquini - slight modification to use case description after phone call conversation with Peter Fox
- March 22, 2007, Peter Fox - conversion to ESIP mediawiki format
Neutral Temperature time series.
Plot the observed/measured Neutral Temperature (Parameter) looking in the vertic al direction for Millstone Hill Fabry-Perot interferometer (Instrument) from Jan uary 2000 (Temporal Domain) as a time series.
- 1.Operation succeeds and user obtains the correct time series plot of neutral
temperature with appropriate axis limits and labels in a form that is easy to interpret and determine that the accompanying data is suitable for a science use.
- 1.Operation fails to return plot in a form that is
easy to interpret to determine data suitability
- 2.Operation fails to find data from the identified instrument operating
in the correct mode.
Schematic of Use case
Use Case Elaboration
This section is intended to be completed with the details of the use case that are required for implementation. This section is not intended to be filled in by an application user.
Scientific user in search of data. The actor that initiates this use case is the portal User. Providers may also initiate this use case.
Security (authentication) actor to identify the requestor and to assist in recording metrics on what data is eventually retrieved so that data providers are alerted as to who accesses their data.
Data delivery actor accepts data requests and returns a data response in a variety of formats (tab delimited, flat ascii, CEDAR binary, OPeNDAP object s, etc.).
- 1.Portal application is authorized to access the backend data extraction and pl
- 1.Datasets in the form of clickable URLs are presented to the user with options for the delivery format
- 2.Downloading version of the plot is also available
Normal Flow (Process Model)
- 1)User signs in to portal application (or otherwise accesses application with or without authenticating)
- 2)User goes through a series of views to select (in order) the desired observatory, instrument, record-type (kind of data), parameter, start and stop dates, and the plot type (should this be inferred?). At each step, the user selection determines the range of available options in the subsequent steps. NB, an alternate path is selection of start and stop dates, then instrument, etc.
- 3)The application validates the user request: first it verifies that the user is authorized to access the specific kind of data, then it verifies the logical correctness of the request, i.e. that Millstone Hill is an observatory that operates a type of instrument that measures neutral temperature (i.e. check that Millstone Hill <isA> observatory and check that the range of the measures property on the Millstone Hill Fabry Perot Interferometer subsumes neutral temperature). Also, the application must verify that no necessary information is missing from the request.
- 4)The application processes the user request to locate the physical storage of the data, returning for example a URL-like expression: find Millstone Hill FPI data of the correct type (operating mode; defined by CEDAR KINDAT since the instrument has two operating modes) in the given time range (Millstone Hill FPI <hasKindofData> 1701 <intersects> TemporalDomain [January 2000, August 2000] )
- 5)The application plots the data in the specified plot type (a time series). This step involves extracting the data from records of one or more files, creating an aggregate array of data with independent variable time (of day or day+time depending on time range selected) and passing this to a procedure to create the resulting image.
- 1.Operation fails to return any valid dates/times. Should instead YYYY.
- 2.Incorrect selection of neutral temperature corresponding to a different instr
ument, or unavailable for the required time period. Should instead be able to generically select quantity without knowledge of how the quantity is labeled in the dataset.
Special Functional Requirements
- Use Case VSTO.neutraltemperature.0.b: Neutral Temperature and Related Quantitie
s Observation= Returns related quantities to the original neutral temperature request.
- Use Case VSTO.neutraltemperature.0.c: Neutral Temperature Observation and Model
Returns neutral temperature from both observations and relelvant model for comparison.
Use Case Diagram
Other Non-functional Requirements
Overall Technical Approach
VSTO architecture diagram: http://vsto.hao.ucar.edu/
Semantic Web - encoding of knowledge about the science domain, quantities and concepts of interest in ontologies and in machine readable form in OWL
Neutral Temperature (is a sub-class of Temperature, which is a sub-class of Temp eratureRelatedQuantity (SWEET)) property of the Earth's Neutral (Middle) Atmosph ere. Fabry-Perot is a type of Interferometer (is an optical instrument which is an in strument), acronym is FPI. Millstone Hill is an Observatory operated by MIT Haystack Observatory and has lo cation N 42.62, W <E2><80><93>71.45 (plus, lots of other properties <E2><80><93>
see Appendix A).
Millstone Hill<E2><80><99>s (MH) FPI (also known as mfp) has two measuring/ oper ating modes <E2><80><93> vertical, i.e. 90 degrees, +/- 1 degree and 30/45 degre es (see reference material). Data in the CEDARdatabase (which is an OPeNDAP-enabled, authentication-required data service) for the two operating modes is denoted by the two distinct kinds-o f-data produced. For the mfp operating in vertical mode, the other parameters measured are: relat ive emission, and neutral wind (north-south, and east-west, and vertical) compon ents. Ontologies are used in step b. to guide the user through the consecutive selecti on steps leading to the final service request. By representing physical instrume nts and their output streams as concrete instances of abstract classes, the appl ication is able to follow the relations between classes (<E2><80><9C>properties <E2><80><9D>) so to always present to the user a range of sensible valid options
that greatly reduces the amount of specific knowledge the user needs to already posses about the data. Although this <E2><80><9C>guided workflow<E2><80><9D> ma
y also be implemented by a more common database technique, the ontological appro ach is more general and allows easier integration of new data sources, possibly belonging to other scientific disciplines. A reasoning engine is used in step c. to verify the logical correctness of the u ser request sent to the service. This guarantees both the request consistency (t he appropriate plot is requested for the given parameter, which is measured by a n appropriate instrument) and completeness (i.e. that no necessary information i s missing from the request). Ontologies are again used in step c. to resolve a semantic data request into a c oncrete expression pointing to the actual data storage, which may be used by any
compliant application to physically access the data.
Protege, Jena, OWl-DL, Pellet, Spring, Eclipse
VSTO workflow VSTO ontology
The Millstone Hill Fabry Perot interferometer is operated by MIT in cooperation with the University of Pittsburgh. The interferometer is located near the Millstone Hill incoherent scatter radar at latitude 42 degrees 37 minutes North (42.62) and longitude 71 degrees 27 minutes West (-71.45). Mean local solar time differs from UT by -(4 hour 46 minutes). The local magnetic field has a 15 degree variation to the West and an inclination of 72 degrees.
Analysis of the data is based on the methods used at the University of Pittsburgh. The analysis is a three step process. First, all the data from the frequency stabilized laser are fit to a parameterized Airy function, producing a table of the instrumental parameters as a function of time throughout the night. Second, a parabolic numerical least squares fitting process is then used on the nightglow data, based on the measured instrumental parameters. This method gives 4 parameters: a doppler shift of the nightglow from the shift in the measured peak, a relative intensity of the nightglow from the signal integrated over the peak, an effective temperature of the neutral atmosphere from the doppler width of the measured spectrum and a continuum background signal from the baseline of the profile. In the third analysis step, the doppler shift of the nightglow line is interpreted in terms of a wind.
Log10 relative emission intensity (parameter 2506) is the integration of the fitted line profile over the free spectral range of the instrument. This is only a relative intensity parameter, intended for comparison of intensities during a single night, or perhaps over periods of a week or two. Changes or drifts in sensitivity are not removed from this number, so comparisons between different nights are not advised. An order of magnitude estimate of the calibration is 10 of these units per rayleigh, however, this is only a very rough approximation.
Typically, a 5 position scan is used: a vertical measurement and 4 measurements at an elevation of 30 degrees from the horizon looking at either the cardinal points or at 45 degrees from the cardinal points. Winds are calculated by measuring the difference in line position between the fitted line and a zero velocity reference. The zero velocity reference is generated by taking all the fitted lines from vertical measurements and smoothing and interpolating them as a function of time. This assumes that the vertical velocity is small compared to the resolution of the interferometer. For nights in which the quality of the vertical measurements is poor, or in which there are not enough vertical measurements for a good smoothed reference, the vertical measurements may be supplemented by an average of measurements in opposite directions. This assumes that the wind field is uniform over the observation points, i.e. without divergences. The method used to obtain the vertical reference is flagged by KINDAT (7001 and 17001 for vertical measurements only, 7002 and 17002 for combined measurements).
Uncertainties in the derived parameters are purely statistical, and do not reflect possible systematic errors. The wind uncertainty is calculated from the data by considering the accuracy of determination of the center of gravity of a line. Temperatures and temperature errors are estimated by taking a fourier cosine transform of the data and fitting the logarithm of the coefficients to a straight line.
When data are taken in the cardinal directions, the winds derived from the measurements are either geographic meridional or zonal. To get values of the horizontal winds at the same time, the measurements are smoothed and interpolated. When data are taken at 45 degrees to the cardinal points, two measurements from orthogonal directions are used to define a vector, from which both geographic and geomagnetic winds are determined. When there are significant latitudinal gradients, the winds are often determined from combining SE and SW and NE and NW so as to keep the latitudinal gradients intact.
References for the instrument and data processing procedures are:
- Biondi et. al., Appl. Opt. 24, 232, 1985.
- Hernandez, "Fabry-Perot Interferometers", Cambridge University Press, 1986.