There is a drive to create an inclusive open data ecosystem, that includes public, private and academic open data [Loenen et al., 2021]. There is a lot of existing research in Open Government Data [Janssen et al., 2012; van Panhuis et al., 2014; Martin et al., 2013] and plethora of OGD in the Netherlands. Although the private sector produces a lot of data, those are not open, as they are not participating in data sharing. In order, to fill the existing data gap, that OGD create, the EU [Commission, 2018], specifically with the Open Data Directive, started to promote more openness in private sector data, especially geospatial data. So far this, it is only done for public undertakings, as a sector in between public and private Boone and van Loenen [2022]; van Veenstra and van den Broek [2013]. The private sector is not bounded by legislation to share their geospatial data.

This research aims to identify what are the challenges to arrive at an ecosystem with more open private sector data, through the identification of the barriers in the process, in relation to the level of openness they are and how to move forward. Five categories of barriers are identified, strategic, technical, legal, economic, cultural and a multi model with 4 levels of openness is used, to identify the current state of geospatial data sharing of 9 companies in the Netherlands. The results show that companies that are providers of data are mostly sharing internally, trying to share with external users, while companies that are intermediaries are mostly sharing with some external users but they are not sharing fully open data yet, and the companies as user of existing open data are difficult to identify. This research demonstrates the influence of the role of the company in data sharing and the level of dataset, project, department in the barriers that the private sector faces and prevent them from sharing geospatial data in the Netherlands.

Currently more than 4 billion people live in urban areas around the globe, a trend that is expected to be increased in the upcoming years. While urbanisation provides the space for innovation and new opportunities, in the meantime physical, technical and social challenges are rising and the cities’ vulnerability is increasing. A tool to tackle these issues are Computational Fluid Dynamics
(CFD) simulations, which can provide insight in various topics.

CFD simulations are valuable for modelling complex urban phenomena such as wind flow, microclimates and thermal comfort. A CFD requires as an input a 3D geometric dataset that represents objects in the urban environment which are most commonly buildings and then according to this input the air flow is simulated around it.

When creating geometries automatically for CFD simulations, several clean up tasks must be completed for them to be usable without any issues. One of the problems arising is related to the redundant faces shared between adjacent buildings, which have no purpose for outdoor flow simulations and cause complications when creating the mesh that is needed for the CFD. This
synthesis project focuses on addressing the aforementioned issue by removing the shared faces.

The ultimate goal of this project was to create an open-source product that can efficiently and in an automated way remove the adjacent faces between buildings. The benefits will be imminent during the meshing process, as we strive to reduce the time that consultancies spend fixing the input geometries before running a CFD simulation, along with an overall improved user experience.

This report is organised in four main sections. The first section is the general introduction of the issue that needs to resolved. The second section defines more in depth the problem and sets the research questions, in accordance to that, in the third section the research methodology is developed. In the fourth section the results of both methods are presented. The fifth sectionfocuses on a reflection of the project, while the sixth section presents the final conclusions. Finally, the seventh section contains the specifics of the project management itself.

The project was carried out in cooperation with Dassault Syst`emes and is developed in the context of the GEO1101 course in MSc Geomatics TU Delft. In addition to this report we have created a GitHub repository (https://github.com/Fabisser/facesBgone) that contains the source code of the two methods.