The validation of a simulation model is a crucial task in model development. It involves the comparison of simulation data to observation data and the identification of suitable model parameters. SLIVISU is a Visual Analytics framework that enables geoscientists to perform these tasks for observation data that is sparse and uncertain. Primarily, SLIVISU was designed to evaluate sea level indicators, which are geological or archaeological samples supporting the reconstruction of former sea level over the last ten thousands of years and are compiled in a postgreSQL database system. At the same time, the software aims at supporting the validation of numerical sea-level reconstructions against this data by means of visual analytics

Dransch, Doris

Eggert, Daniel

Klemann, Volker

Rabe, Daniela

Unger, Andrea

English

OceanRep

Slivisu User Manual1Table of ContentsTopic PageDescription 3Supported Data Format 4Connecting to Database 101. Exploration of Observation Data 121.1 SLI-Hierarchy 131.2 RSL Categories 151.3 SLI Table 231.4 Sea Level Curve 261.5 SLI Time Histogram 351.6 Time Scale 411.7 Map 432. Exploration of Model Data 522.1 Scatterplot Matrix 542.2 3D Scatterplot 562.3 Scatterplot 582.4 Model Histogram 612.5 Model Table 652.6 Fit Scale 673. Brushing and Linking 71 2Slivisu - A visual analytics tool to validate simulation models against collected dataTo support the scientists in gaining insight into the data and the consistency between data and model, Slivisu was developed to fulfil the following tasks:Making apparent• the distribution of collected data over over space and time• the various quality measures of the collected data• the difference of calculated and modelled data in space and timeA combination of methods from analysis and visualization is applied in the concept to support the tasks:• The Sea Level Indicator (SLI) data are clustered according to the collection process or data availability; the cluster is presented by an adaptive convex bounding box.• All information about the SLIs in a cluster is summarized in a multivariate summation diagram which depicts the number of SLIs of a certain quality in various time intervals• Information about single SLIs can be presented interactively on demand3Supported Data Format4For full functionality create a table rsl.slivisu_attribs which connects the native column names to those expected in slivisu. There, the information can be placed for different tables inside the database.• PostgreSQL DB• Example:Observation Data5The following attributes are optional. If the attribute does not exist, or the entry is empty, they are calculated from the respective equation below in the program.Observation Data6• External data ahead of the database can be read in.• SLIVISU/selection/blub.sel or SLIVISU/data/blub.lis• Selection, .sel• Selections, that can be loaded or saved are newline separated lists of gid's in files ending with sel. These will be marked in the views, if the respective SLIs exist in the Listing. If not, the loaded selection is reduced to those gid's. But keep in mind, that with improper ending the file content is ignored.• Parameter listing, .lis• A parameter listing is provided in .lis files, which contain for a set of models the parameter values and filenames where RSL predictions and calculated fits or deviations at the respective SLIs are given.Model Data7.sel Files:• newline separated lists of gid's in files ending with selModel Data8.lis Files:• num is the number of parameters or dimension of the parameter space.• name# gives the annotated name in the respective view,• min# and range# gives the minimum value and range of the respective parameter for the representations in 'cube' and the other parameter charts and matrix.• In the following data list, the first column gives the filename which is considered relative to the directory where the .lis is located and the following columns, 2, ..., num+1, give the considered par for each model.• The parameter name and arrays are due to the name space used in this program, as the type definition follows after # at the beginning of each line. s is string, d and f is for double and single float.Model Data9Connecting to Database10• Observation Data DB:• Choose parameters on start• When using a different database, the login of course has to be modified, but in the respective theme a table like slivisu_attribs has to exist, which relates the attribute names of the respective table containing the data to the column which is interpreted in SLIVISU.• Click on Test Connection, green = connectionestablished, yellow = connecting, red = connectionfailed• Save & Connect to start111. Exploration of Observation data121.1 SLI Hierarchy13SLI Hierarchy:The hierarchy describes a regional definement inside a table• Database (complete SLI Database)• SQL-Table (in this case: ant) • Table (tab_name, in this case: Antarctic Pen)• Subregion (curve, in this case: South Shetland Islands)• Single SLI (ant_-00538)[0/4/581] =  0 SLIs marked, 4 selected, 581 total• Select a subset of SLIs by selecting hierarchy levels or single SLIs:• Selecting a checkbox automatically selects every SLI on sublevels• to unfold sublevels click on the circle next to the checkbox141.2 Sample Categories15• The four default categories upper, lower, band and none are automatically selected on start• upper: SLIs with given rsl_max and empty rsl_min• lower: SLIs with empty rsl_max and given rsl_min• band: SLIs with given rsl_max and given rsl_min• none: SLIs with empty rsl_max and empty rsl_min• to edit a category or define new categories click on Edit16Category nameSQL query17• Select category name, color and an SQL queryto define SLIs for the category• the List of attributes shows possible columnsand their types• Click Save as... when doneSave your category file in SLIVISU/filter18Load your category file and select your category19CSV Files• should be located in SLIVISU/filter/mycsv.csv• the querys are stored seperately in SLIVISU/filter/sql• they can be edited in any text editor too• Example default.csv:Category NameCategory Coloractive y/nPath to ImagePath to Query File20Query Fileselect from sli where cat = 'upper'• SLI color depends on it's category. The priority is from left to right, you might need to deselect the defaultcategories or reorder them to see your category in the other views• To do so click on Order• Click and hold a Category and move it to it's new place• Click ok when done2122• Your RSL Category is now visible in other views• SLIs without any category belong to category "none"1.3 SLI Table23• SLI Table contains all the information from the database for the selected SLIs plus their categories• yellow columns are marked SLIs24• sort the table by clicking on a column header• to select or deselect SLIs in the SLI-Table click on their row (ctrl + click for adding SLIs to the selection)• or write a SQL-Query in the field and click on Start Query, this will automatically mark all fitting SLIs in theopen table• Invert Selection inverts the selection• Right Click opens the pop-up menu:• Show only Selected hides non selected SLIs in the SLI-Table• Invert Selection inverts the selection• Reduce to Selection does not work on more than one table! Other tables will be closed.251.4 Sea Level Curve26• Sea Level Curve for individual samples• X: uncertainty interval of time point• Y: uncertainty interval of value (height)• Color: interval type / category27• Select by clicking and drawing a rectangle over the shapes• Marked samples are yellow• right click on the slider opens the edit menu where max height and min height can be adjusted• adjust the scale on the right to view only SLIs within the selected height range by moving the sliders28Right click opens the pop-up menu29When Only selection is checked, only the marked SLIs are shown30When SLI-category differentiation is unchecked, only the marked SLIs are shown in their category color, other SLIs appear dark grey.31Shape types changes the form of the SLIs, default is line object 132line object 2 line object 3geometry object 1 geometry object 233• When show model(s) is checked, the model points are shown with their Goodness of Fit color• show average fit shows them in the color of the average model fit• Export to LIS-File: save the selected SLIs in lis-Format3435Lis Format for Sea Level Curve::model fit and height(only if at least one model is selected)1.5 SLI Time Histogram36• Number of samples in a time interval grouped by type• X: Time, Y: number• yellow overlayed parts show the number of marked samples in the category/time interval37• A tooltip shows details about the category and the time interval by hovering the mouse over• Selection of bins with click or ctrl + click38Right click opens the pop-up menu3940The number of Bins can be adjusted from 1 to 30Number of Bins = 10 (default) Number of Bins = 15Number of Bins = 5• Check Only selection to see only marked SLIs in the histogram• Check Marked SLI in seperate bar to see the number of markedsamples inside a time interval in a seperate bar41• Unchecking SLI-category differentiation shows total count only• Unchecking Show total count bar removes the grey seperate bar (in combination with marked SLI in seperate bar)• Export to LIS-File: save the selected SLIs4243Lis Format for SLI Time Histogram::1.6 Time Scale4445• Move the sliders in the Time Scale to adjust time rangefor the Sea Level Curve and the Time Histogram• Right click opens a menu to change the number ofsegments1.7 Map46Spatial distribution of samples and sample groups 47• The name of a SLI or curve is shown at the top by hovering over it with the mouse• "Grab" the map with the left mouse button to pan it• Zooming is possible with the mouse wheel 48• select a (sub)region by clicking in the polygon• or select single SLIs by clicking (ctrl + click adds SLI to selection)49• After reading in model data, the layers for regions will have the average fit color (see Fitscale)• SLI points keep their category color• to see their goodness of fit color select Model Fits from the pop-up menu (right click)• on selection of indicators in SLI Table, the fit is not adjusted here, but depends on the SLIs existing in  the table50• Check Selection only to see only marked SLIs• Chose Export to LIS-File to save the selected SLIs 5152Lis Format for Map::model fit(only if at least one model is selected)• Click on Layer in the lower left corner to open the layers menu• tab: Polygons for the tables (SQL-Table)• tab_name: Polygons for the regions (tab_name)• curve: Polygons for the subregions (curve)• flags: show goodness of fit histogram• SLIs: SLI points5354Time from past to present• color = goodness of fit• length = number of SLIs in time interval552. Exploration of Model Data56To load a model data file• click on Program → Import Model Data• (s. Model Data)• select the file from the menu• click on Load LIS-File• while the file is loading the status isshown in the status bar below572.1 Scatterplot Matrix58• A Scatterplot Matrix for the model parameters• Moving the mouse over an instance shows details as tool tip592.2 3D Scatterplot603D Scatterplot• Axes: model parameters• Cubes: model instances• Cube color: aggregated goodness of fit• Turn the cube with the keyboard as shown in the graphic above (or with the mouse, X-Axis only)• Reset brings the cube back in the defaultposition612.3 Scatterplot62Scatterplot• The selected plot from the Scatterplot Matrix in detail• Moving the mouse over an instance showsdetails as tool tip63Right click opens a popupmenu with the view settings.642.4 Model Histogram65Model Histogram• One histogram for each model parameter• X: parameter value• Y: stack of model instances sorted by goodness of fit66• Moving the mouse over an instance shows detailsas tool tip• Select a model instance by clicking on the square• A yellow frame shows which instance is selected• Ctrl + click to add further models• Unselect by clicking outside an existing model67Right click opens a popupmenu with the view settings.682.5 Model Table69• Model table containing all the information from the model data file plus the model fits• yellow rows are marked model instances• In the model column, the color shows the average model fit for the selected SLIs• sort the table by clicking on a column header• right click opens the pop up menu where the fit column can be chosen702.6 Fit Scale71The Fit Scale shows• which norm is used to calculate the goodness of fit• the color scale for the goodness of fit• click on edit to open the settings menu• min/max: scale range, default it 0 to 1.2• Colorscheme: colors for the goodness of it, default isred• segments: number of different colors, default is 6• norm: Fuzzy: 1- norm, Euclid: 2 -norm, p-Norm:7273743. Brushing and Linking7576BRUSHING AND LINKING• Select data (SLIs, Model Instance)in one view• See selection in other views77BRUSHING AND LINKING• Example: selecting a subregion in the map...78BRUSHING AND LINKING• See selection in other views.• Example: Check Reduce toSelection in the table Pop-Up...79BRUSHING AND LINKING• SLIs are reduced to formerSelection.• Example: pick a model instance...80BRUSHING AND LINKING• See model data in other views.• Explore!

A visual analytics tool to validate simulation models against collected data. V. 1.0.0

http://oceanrep.geomar.de/49496/1/slivisu_usermanual.pdf

A visual analytics tool to validate simulation models against collected data. V. 1.0.0

Abstract

Similar works

Full text

Available Versions

OceanRep