Restore Session Help Page

To restore a case study you previously worked on, you choose "restore Session" on the main menu.

PoMM Main Menu

Restoring a previous Session on the Case Study Lab

Users can restore a previously started session by reloading the files saved

1. in the first setup phase of the case study, or
2. from the files saved at the end of a session.

The folder saved as a .zip file at the end of the first phase has the following structure

|-UnityOfAnalysis |---nbs_xyz.jpg |---data_abcd.json |-Notes |---notes_first_abcd.json |-Entities |---selected_entities_abcd.json |-DecisionProcessFlow |---diagram.png |---diagram.bpmn report_abcd.docx

Select the geographic code (NUTS) of the Unit of Analysis

NUTS are statistical codes to define a geographical area. To reference countries’ regions for statistical purposes, the EU has developed a classification known as NUTS (Nomenclature of territorial units for statistics). In PoMM, NUTS are used to associate geographical location with administrative location. More information on NUTS on the EU website → https://ec.europa.eu/eurostat/web/nuts/

By selecting the level (0,1,2,3) you choose to place your analysis at a national, macro-regional, regional or provincial level respectively. Only by selecting level 3 (provincial) is it then possible to also choose the further level LAU (Local Administrative Unit) which is typically that of operational interventions on NBS.

Choose the NBS(s) considered for the experiment

The NBS catalogue and the tool that helps making a reasoned choice is available outside the PoMM. It is assumed that such analysis has already been made before using the PoMM.

Choose the CEC(s) considered for the experiment

It is assumed that such analysis has already been made before using the PoMM.

Notes on the reasoning behind the definition of the Unit of Analysis

Always keep track of the reasons and justifications for your choices.

This will come in handy later when you need to explain, for example, why you've chosen to look at a whole family of pollutants rather than a specific one.

It is also useful to remember that the analytical approach changes if you place your observations at a regional or higher level, from where you may decide not to go into much detail and therefore use the Not Applicable option.

But remember that you must select at least one target CEC (or CEC family), because that's what the PoMM is all about.

Describe the decision-making process you want to analyse

Draw the decision process by creating a new BPMN diagram.

As you draw the process, keep in mind the central policy issue you are dealing with.

You can also use an existing BPMN diagram and drag and drop it here.

If you use a diagram created outside of PoMM, make sure it's in a compatible format, otherwise you'll get an error message.

You can replace a diagram by simply dragging and dropping a new one, but before you press NEXT!

Remember to add an annotation (note) to the entities you consider potentially interesting for the subsequent modelling and simulation of policy decisions and interventions on them.

These annotations will be used to construct the map of the decision-making workflow you want to analyse.

An annotation should give the name of the main variable associated with the entity that you want to investigate in your analysis. You can have more than one annotation (variable) associated with an entity.

The variables should be chosen or described so that they can be measured in a minimum to maximum range.

If you annotate a graph that you later replace, your annotations will be lost.

When in doubt, always consult the Help.

Identification of the most important entities

In this step, you select the most important entities that you want to deal with in the subsequent modelling and simulation.

The entities you see here are those you have marked as annotations in the previous process diagram (BPMN).

You must select each entity you want to bring to the further step of analysis. The entities you select change colour to red.

In order to have a sufficient overview of the model you are experimenting with, it is best to have a maximum of 12 nodes.

If you are dealing with the problem at a high level, 7 is often enough (if they are well defined).

In the next phase you can still remove or add nodes. But you can't go back.

If you want to change the BPMN diagram, you have to start from the previous phase.

Notes on the reasoning behind the definition of the decision workflow

This text will be included in your report.

Once again, always keep track of the reasons and justifications for your choices. This will come in handy later when you need to explain, for example, why you've chosen some concepts (variables) as your focus of investigation instead of others.

It will be very helpful also to keep your journal when you go through analysing you context from different points of view (the politician, the developer, the public manager, etc.).

If don't keep track of why and how you contour your domain of observation it will be very hard to make comparisons later.

But, if you do not need or want to write anything, you can keep the default text or delete it.

Notes on the reasoning behind the identification of most the important entities

Notes on the reasoning behind the identification of most the important entities

The annotations refer to the variables considered important or critical for the issue of policy making / decision making under consideration.

Download the Intermediate Report

The Intermediate Report describes what you've done until this step to outline the Case under Study and set the boundaries of your Experiment.

The work done will be saved in a .zip file so that you can restore your session from this point on, if you need so, choosing the 'RESTORE SESSION' on the start menu.

As a precautionary measure, the PoMM requires you to download the Intermediate Report and the back-up files to grant you access to the next step.

Mapping how much important entities influence each other

The next section concerns the creation of the cognitive map from the most important entities previously selected. Pressing the “LOAD” button in the upper-right interface will load the entities onto the board.

You will be able to link them together by pulling an arrow from the entity of your choice.

Clicking on an entity will open a sidebar on the left side of the screen, where you can enter a variety of information about it (this is not mandatory).

Once you have defined the influence relationships between entities by linking them together, you can continue to the weighing step by pressing the “NEXT” button in the upper right corner.

For more comprehensive explanations, consult the manual via the help button.

Running the experiment

Understanding the model: Network Analysis of the map

The first step is to examine the topology of the network just designed, before setting its initial state.

This is a static network analysis of the model, and tells, at least:

• which entities (nodes) are influenced but do not influence any other; possibly these are either the ultimate effects to be observed, or targets to achieve;
• which nodes on the contrary do influence other nodes but are not influenced; possibly these are drivers, root causes;
• how much is a node connected (how many connections it has, both inbound and outbound); the centrality of a node give an idea of its visibility to other nodes, though not necessarily importance in a dynamic behavior.

Many other network analysis indicators can be computed, but network analysis observes the static layout of the map, which instead is used dynamically for simulation (actually it is a neural network).

Setting the initial state of the model (the map)

Here you can define the value of the initial states for the simulation of the do-nothing scenario.

It is possible to assign a value to more than one entity.

Remeber to leave unchanged (you must set = 0) your observables, that is the entities for which you intend to evaluate the effect of the simulation.

Simulation and analysis of behaviour without intervention (do nothing case)

Analysing the behaviour of the modeled system without intervention (do nothing case)

Simulation and analysis of behaviour under different initial conditions (What if)

Analysing the behaviour of the modeled system without intervention under different initial conditions.

To run a new simulation with a different initial state, go back and re-set the variables.

Keep in my mind that if you go to next section (intervention), the latter state is considered for intervention.

Notes on the reasoning behind simulations and reflections on outputs

The experiment defined the data of the initial conditions that we established as the reference situation.

The observable quantities were also identified.

A simulation was then carried out to examine the equilibrium state of the system considered in the reference situation.

The interventions were then applied to the critical variables.

The simulations allowed us to examine and compare the effects of the interventions on the behaviour of the system with respect to the reference situation.

The intervention configuration considered optimal was chosen.