\section{Introduction}

The project's goal is to produce a program for the University of Helsinki's spatial data analysis research group. The program analyzes spatial data by using a prior distribution and a mathematical model to calculate the posterior distribution for a set of variables. The posterior distribution could for example be a bird species' distribution in Finland. The program will not analyze how accurate the given model is, it will only calculate the posterior distribution. Model comparison will be done with other software using the posterior distributions as data.

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\subsection{The problem domain}

The main topic of interest is the question about the most accurate model to describe a given real life phenomenon. The only way to compare the models is to compare the results. Defining a general modeling language is hard, implementing a program to process data using a general model is even harder. The PIANOS project will concentrate on producing a program for processing two given datasets. This cuts back the amount of needed features in the modeling language.

The simulation needs a large number of iterations before the results start to converge on certain points. Due to the number of iterations and large data, the calculation might take a long time to finish. This requires the program and the implementation language to be efficient.

\subsection{Previous systems}

The software is related to another currently in use, named Bassist: `Bassist is a tool that automates the use of hierarchical Bayesian models in complex analysis tasks. Such models offer a powerful framework for modeling statistically complex real-world phenomena.' [Bass]

Currently the research group is using BASSIST to analyze spatial problems. BASSIST was not designed for problems with spatial dependencies. Its modeling language lacks features which would allow efficient definition of spatial problems. The goal is to concentrate on a small subset of spatial problems which cannot be solved efficiently with BASSIST.

\subsection{The problem domain in diagrams}

This section aims to provide a high abstraction level map of the problem domain. 
It is a set of ER-diagram-style maps of the domain as the project members see it.

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\caption{The simulation parameters}
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