Terminology

General Terminology

Modeling hub
a consortium of research groups working together on a common set of modeling tasks to develop ensemble models to provide stakeholders with a single model output representing uncertainty across different modeling assumptions and frameworks.
Team
a group of individuals developing modeling software to generate models in response to tasks coordinated by modeling hubs.
Configuration file
a file that is required to define specific aspects of a modeling hub such as administrative information (contact information, license, time zone, data storage availablility) and information concerning model tasks. These files are constructed by the hub administrator using the hubverse schema.
Metadata
a file or series of files with structured information describing the general characteristics of the object they reference. For instance, model metadata files describe the characteristics of models contributing to a hub.
Schema
a declarative format used to organize and set the structure of other data, including required and optional fields. Schema define the specifications for the configuration files that are required to be present in a modeling hub.
Zoltar
a research data repository that stores forecasts made by external models in standard formats and provides tools for retrieval, validation, analysis, comparison, visualization, and scoring.
Mathematical model formulation/structure
a statistical or mathematical formulation of a model.
Modeling software
code that implements a team’s mathematical model formulation/structure to generate model outputs. Each team may have multiple instances of software.

Modeling Tasks Terminology

Learn more about modeling tasks

Target
a quantitative outcome of interest for a modeling hub. For example, “incident case counts.” Targets typically (and sometimes implicitly) refer to a value of an observable variable in a given window of time, a given location, and possibly other stratifications (such as age group).
Model output
a set of target results in tabular format generated in response to some modeling task for a specific round. A model might result from a single team’s response to the task or from an ensemble of results representing the outcomes of multiple efforts.
Round
a time period for which a set of specific model outputs are solicited. Rounds define the “cadence” of submission for a modeling hub. For example, some hubs might accept daily submissions, where each day is considered a different round. Other hubs might have one round every month, with a submission period that may be open for multiple days.
Task
a definition of the goals of a modeling effort, possibly including conditions, assumptions, and targets (collectively known as task ID variables). Some tasks may be fixed across rounds, such as for forecast hubs that regularly solicit predictions for a set time horizon in the near-term future. Other tasks may be more variable; for example, those in scenario hubs that model hypothetical futures with different assumptions for different modeling rounds.
Task ID variables
a collection of conditions, assumptions, and potentially targets that are used to parameterize a model task. These represent columns in the model output. A more detailed explanation of task ID variables can be found in the documentaiton.

Prediction Terminology

Figure illustrating the difference between nowcasts, forecasts, and projections showing a timeline of weekly incident case counts from February 2020 to early March 2021 with projections from April to September 2021. The range from the graph's beginning to March 2021 is labeled "Surveillance Data." The "Nowcast" range covers three weeks of preliminary surveillance and projected data with confidence intervals. The "Forecast" range has no observed data and covers the next four weeks with four slightly diverging model estimates and confidence intervals. The "Projections" range covers the period between May 2021 and September 2021 and shows the models' confidence intervals.

Figure credits: Alex Vespignani and Nicole Samay of the Scenario Modeling Hub
Nowcast
model output that provides estimates/predictions of partially observed or unobserved values at the current date from a data stream before the current date. Nowcasts should be set up to be evaluated for accuracy based on comparisons with the eventually observed complete data. See the horizons nomenclature image above.
Forecast
a specific quantified prediction of an observable event or trend that has yet to be observed, conditional on data that has been observed up to a specified time. Forecasts should be set up to be evaluated for accuracy based on comparisons with the observed data. See the horizons nomenclature image above.
Scenario
a description of a possible future to be modeled, described in terms of model parameters that might be varied, such as transmissibility, vaccine adoption, vaccine efficacy, the emergence of a new variant, etc.
Scenario projection
model output that provides estimates of future observations of future trends conditional on specific assumptions about a given scenario. Scenario projects are challenging to evaluate against future observed data since the assumptions under which scenarios were generated likely will never have been exactly met. See the horizons nomenclature image above.

Abbreviations

The hubverse code often has abbreviations which may not be familiar to users. This page provides a list of abbreviations and their meanings. Let us know if we missed any by filing an issue on the hubverse site GitHub repository.

abbreviation meaning
abbr abbreviation
cdf cumulative density function
cdn condition
cfg config/configuration
col column
eq equal
exec execution
fn function
gt greater than
gte greater than or equal
id identity
idx index (of an array)
lt less than
lte less than or equal
mt model task
out output
pkg (R) package
pmf probability mass function
popn population
pr pull request
prop property/proportion (depending on context)
spl sample (from a distribution)
taskid task ID
tbl table/tibble/data frame
tid output type ID
tmpl template
ts time series
val value