Integrated Data Analysis for Parametric Design Environment mineR: a Grasshopper plugin based on R Abdulmalik Abdulmawla 1 , Sven Schneider 2 , Martin Bielik 3 , Reinhard Koenig 4 1,2,3 Bauhaus-University Weimar 4 Bauhaus-University Weimar and Austrian Insti- tute of Technology 1,2,3,4 {abdulmalik.abdulmawla|sven.schneider|martin.bielik|reinhard.koenig}@uni- weimar. de In this paper we introduce mineR- a tool that integrates statistical data analysis inside the parametric design environment Grasshopper. We first discuss how the integration of statistical data analysis would improve the parametric modelling workflow. Then we present the statistical programming language R. Thereafter, we show how mineR is built to facilitate the use of R in the context of parametric modelling. Using two example cases, we demonstrate the potential of implementing mineR in the context of urban design and analysis. Finally, we discuss the results and possible further developments. Keywords: Statistical Data Analysis, Parametric Design Introduction Design is a cyclic process aimed on finding an opti- mal solution for a given problem. This process can be broken down into two stages: First, finding an acceptable initial design plan that might provide a baseline for the desired solution. Second, further de- velopment and optimisation of the initial design plan into an implementable design solution (Karimi 2012). In this process, the design generation is informed by design evaluation in a series of successive steps - the design cycle. Since each step aims to further improve the design, it is important that the design workflow promotes ease of transition between the generation and evaluation. During the recent years, paramet- ric design has emerged as a quantitative design ap- proach that connects the parameters for generating and evaluating a design via algorithms to shorten the optimisation cycle and providing the designer with an access to the data throughout the design stages (Motta 1999). Parametric design approach is usu- ally connected to programmable tools that have the capacity to generate and manipulate complex data. These tools help assign values to the design parame- ters as well as optimize the design to satisfy specific criteria. To test and analyse a design, designers ap- ply evaluation methods for different design criteria. Some of these criteria are more qualitative and can be PARAMETRIC MODELLING | Applications - Volume 2 - eCAADe 36 | 319