Explore | Glossary
Glossary
Data Inputs
Data inputs are various pieces of information and variables that are used to run an optimization process. These inputs can include numerical data, qualitative information, and other relevant factors that influence the optimization model. Data inputs provide the necessary information for the optimization algorithm to evaluate and analyze. By providing accurate and reliable data inputs, the optimization process can be fine-tuned to provide the best possible outcome.
These inputs act as the foundation for the optimization model, allowing it to make informed decisions and generate optimal solutions. Overall, data inputs are essential in enabling an optimization process to find the best possible outcome by considering various factors and variables, ultimately leading to improved efficiency, cost-effectiveness, and performance in a wide range of industries and applications.
Priority Places
Priority places are the boundaries of the places that are a specific geographic focus for you. The datasets included here outline several possibilities for selecting areas that are interesting for understanding the optimal areas to place funding and effort. This will vary depending on your organizational priorities but could include landscapes with a species focus, particular habitats or ecoregions (forests, grasslands, etc.), or political jurisdictions where you know or want your work to be implemented.
Scale
The scale is the base area on which optimization is calculated in PIE. They represent continuous and adjacent geographic boundaries within which actions take place. These might be the scale at which decisions are made in landscapes (e.g., at the watershed scale) or a user might select an equal area geometric scales (hexagon or pixel) to standardize the optimization results. The model will determine whether each scale is optimal or not across the entire surface of each priority place.
Actions
The “Actions” is a layer that describes where an action is possible within an priority place. The layers provided here are global datasets that indicate, to some extent, where an action in a landscape is possible. It is likely that the conditions around where the actions you would like to take are possible will be further constrained be the projected realities of implementation and in the future uploading project-specific data on actions will be possible. Generally, the layers included here identify places where degradation has occurred, where natural land cover has been converted, or where the opportunities for a specific intervention (e.g., tree restoration) are predicted to have potential.
Initiatives
Initiatives are the factors that train the optimization of impact potentials towards areas that are important for other environmental or social objectives. They help ensure that PIE not only optimizes the places that can have the most impact based on the impact potential datasets, but qualify that whether a place is optimal or not is also reliant on the contribution that a scale can made towards addressing other objectives of your organization that might not be entirely captured by the impact potential datasets. Here, there is the opportunity to better ensure that actions taken in future implementation of project work take place in places that matter for people and nature.
Learn more about Initiatives in the Explore area of the tool.
Impact Potential
Impact potential refers to the estimated change between a baseline value and the maximum value for a variable in a place. In PIE, the impact potential datasets include the potential of places to support a reduction in threats to biodiversity, to limit soil erosion, to sequester carbon, and to minimize the opportunity cost of non-agricultural production land uses. These data demonstrate the potential value of a place in making improvements to these variables. However, there are often trade-offs among objectives like these and PIE provides guidance on the best places to achieve multiple, optimized improvements in these variables, improving efficiency of investments and likely limiting trade-offs.
Learn more about Impact Potentials in the Explore area of the tool.
Case Building
Within PIE, users can build cases primarily to explore areas that might be optimal for their investments in conservation, restoration, or improved management work. Cases are the individual execution of a PIE assessment based on the selected inputs. PIE allows users to generate these cases from drop-down menus that contain a wide range of relevant data that helps explain what they would like their investment to achieve. Cases and Collections of cases are managed in PIE's Optimization Manager.
Optimizations Manager
The Optimization Manager is the functional center of PIE. Here users select inputs for the optimization based on their objectives. Here, they build cases for analysis that include geographies and the data that best align with their project or investment objectives. Once cases are complete and all requite data are identified and selected, users can return to the optimization manager overview page to run the PIE optimization on the case they are interested in generating results for.
Collections
Within the optimizations manager, collections refer to groups of optimization cases. The rationale for collections is that within PIE, as users explore the optimization of their conservation or restoration portfolios they may wish to tweak components of each of the optimizations without changing other components. For example, a user could select 4 countries of interest for the optimization and an action that describes where conservation or restoration work is possible, but may want to understand how selecting different beneficiaries or decision units may change the output of the analysis. “Collections” are a method of organizing and saving the different version of an optimization that may be interesting to a user as they explore PIE.
Cases
Optimization cases refer to a single output of a PIE optimization following the successful input of all required data and an execution of the analysis. Each case will have unique results and a unique combination of Priority places, Scales, Actions, and Beneficiaries. It is also possible to add a case as a favorite if it has produced results that are especially useful or interesting.
Optimization Runs
An optimization run is the execution of the PIE optimization tool with the data inputs defined in a case. The processing time will vary based on the area of analysis and the number of beneficiaries selected. For example, an analysis of Ethiopia using the three impact potential datasets and one beneficiary layer requires roughly 10 minutes to complete the model. Here runs can either produce results or fail to produce results if the combination of data selected is too large to compute. We recommend that users target their runs and cases to geographies of particular interest and not broad areas and several large countries. For this reason we have included “regions” as a potential geographic area of interest input.
