Entering Data

Interacting with SISEPUEDE

Category Attribute Tables

Variable Attribute Tables

Attribute tables are fundamental components of the data framework underlying SISEPUEDE. Attribute tables define sectors and categories associated with those sectors (those starting with cat_); model variables and associated attributes, including variable schema (which include information on units–those attribute tables starting with

Design Region Strategy Time Period

See Dimensions of Analysis for more information on the dimensions of analysis and what they control.

The SISEPUEDE framework relies on a collection of tools and classes–including the InputTemplate, FutureTrajectories, SamplingUnit, and LHSDesign classes–to represent input data, including uncertainties and levers, and modify them to facilitate robust exploratory modeling (see Entering Data for more information on these classes)

Variable Name

Variable Schema

The $VARNAME$ notation to denote metavariables as components of variable schema. These variable schema are used to store data in the model_input_variables.csv file.

For example, model input variables used to denote agricultural activity emission factors by crop type and gas in model_input_variables.csv may have the following structure: ef_agactivity_$CAT-AGRICULTURE$_$UNIT-MASS$_$EMISSION-GAS$_$UNIT-AREA$, where

$CAT-AGRICULTURE$ is the categorical crop type (e.g., cereals, oil crops, pulses, etc.);
$EMISSION-GAS$ is the greenhouse gas that is being emitted (e.g. co2, ch4, n2o, sf6, etc.)
$UNIT-MASS$ is the unit of mass for gas emission (e.g., kg for kilograms; some sector variables may use gg for gigagrams);
$UNIT-AREA$ is the area unit (e.g., ha is hectares).

These components are referred to as metavariables–they characterize and describe the notation for naming model input variables. Each variable is associated with some naming schema, which presents a standardized format for variable entry depending on the relevant metavariables.

Note

Example: the $\text{CO}_2$ emission factor for maize crop production, which captures crop burning, decomposition, and other factors, would be entered as ef_agactivity_maize_kg_co2_ha since, in this case, $CAT-AGRICULTURE$ = maize, $EMISSION-GAS$ = co2, $UNIT-AREA$ = ha, and $UNIT-MASS$ = kg. Similarly, the $\text{N}_2\text{O}$ factor, which includes crop liming and fertilization, would be captured as ef_agactivity_maize_kg_n2o_ha.

Simplex Group

Simplex groups are unique to each attribute table and are entered in the Simplex Group field as integers. This marker allows users to specify variable trajectory groups on a standard simplex with a flag. Which fields must sum to 1 are defined by how the groups are entered:

If one variable is associated with a unique simplex group (i.e., 1:1), then the sum of all fields associated with that variable must equal 1.
If multiple variable are associated with a unique simplex group (i.e., one simplex group maps to four variables), the the sum across variables must be 1 for each category across the variables.

Simplex groups cannot be specified outside of a single attribute table.

Input Templates

Each region has a template for each sector
five templates
3 different types: calibrated, uncalibrated, demo

Defining Futures

Defining Strategies

Variable Trajectory Groups

Variable trajectory groups allow users to specify collctions of variables that will vary using the same Latin Hypercube Sample. There are two approaches to defining

Defining a Variable Trajectory Group using the Bound-Mix Approach

($b_0$, $b_1$, $m$)

Defining a Variable Trajectory Group using Trajectories Alone

Users do not have to use trjaectories

Note on Variable Trajectory Groups and the Standard Simplex

Sampling Units

SamplingUnits represent variable or collection of variables that are perturbed by a single Latin Hybercube (LHC) sample. There are a number of ways to define sampling units in the input templates.

… describe approaches here