Science 4 Policy makers

Science is the continuous curiosity of the human to understand the world it realises, and often the findings or the knowledge it gains transformed into technology to improve its life.
One of the "products" of Science is to help those who determine the policies that will be implemented. Policies could be, for example, digital transition or even environmental protection. Policymakers should start with the questions that need to be formulated (the questionnaires) to collect the data to determine the needed directions. The policies will apply to society and should be responsive to all layers of society to be more realistic, and citizen participation is essential. Citizens should understand that Science is for them and participation is for the good of all. Therefore Science can help them understand society and the world better, so there are models that simulate certain situations so that decision-makers can build the most appropriate questions.

Maybe today with the data that exists from digital devices it would be worthwhile to have a mechanism for constant updating, --somehow as a Digital Twin with society from all layers and then what we really require is to examine the evidence(the data)

.


/// Our world ... so complex, and with the knowledge we gain over time, we should manage these complexities and uncertainties as citizens. Simulations are an essential tool to minimise the uncertainties we have. Simulations will need data to support policymaking. The involvement of citizens is essential, and they will need to trust and understand the processes and their perceptions. The data source is important, and it will be important to consider how the data was collected and what treatments have been done with the data. Professors can use these data to assign tasks, even citizens to validate what decisions are being passed or even science to repeat the same experiments and confirm the results ... Policy Makers' Policy creation is responsible for asking the right questions and the way the questions are asked. Depending on the audience, there is an appropriate format and language. Policy creation is a complex and demanding process that sometimes social groups need to be considered to treat the establishments accordingly. Simulation models help analyse these policies, and then it will be policies based designs for those making the decisions to ensure that they are based on realistic information //
and the policies should be based on:
1. rely on udderline logic
2.How use The data z
3) What is the constraints and assumptions to form the models. What are the assumptions and limitations of the models?

All these are the tools that have the effect of forming the questions to lay the foundations for policy making and to understand what a model can and cannot do as well as ownership.We want to know the assumptions and the limitations, it should be clear in a transparent way. Models are a simulation of the real world if we change something then the change should also reflect the real world. That is, models are not static but change over time sometimes evolving into other models either to cover the changes or to correct the previous ones. It is important to mention that some variables and situations will be outside our models , these should be mentioned in the documatation of our tools. All these tools the European Union plans to integrate them into the MIDAS tool for policy making. Of course, we should mention that if we have great and enough data that is being constantly updated, we may not need to create models but to examine continuously the data generated. What are the inputs and outputs of the models. The quantification of the data but also what is going to be left out of the analysis. The uncertainties how they affect our models , the transparency but also the methodology we applied but also the limitations, there are we could use the expression from George edward box "all models are wrong but some are usefull". The models are derived from the real world, besides the transparency that is necessary and communication is needed, the citizens should understand as much as possible, therefore simplicity is important, what better when we can describe this complex world with simple understandable models. Our models should have the following.

1. scientific credibility: level of trust and reliability
2. salience: the property of something that makes it stand out or attract attention in a scientific context.
3. endurance: the ability to perform scientific tasks or activities for a long time without getting tired or losing focus.

As scientists, part of our job is to create experiments and models, but they have to be effective, and this takes time to develop methods and techniques. Sometimes people ask more questions than the model can provide and because as scientists we want to answer but our models can't and sometimes we have to go out of our way to create models. Science and models are an input to policymaking but there are so many other considerations that determine the outcome that they can be disappointing and there will always be political considerations. In addition every model that is reconstructed has some politics and limitations depending on the data it is easy to model nature and the environment we have a lot of data. Unlike the social aspect in human behavior cannot be predictable. Maybe some predictions could be made on groups of people to predict behaviours. Finally, it is important for the interventions we make in models other than people to observe the change in behavior.