## 1 Introduction  
As stated by the Energy 2020 strategy, the reduction of Greenhouse Gas (GHG) emissions in the European Union (EU) can only be achieved if tackling appropriate the big potential existing when increasing energy efficiency [1]. This is particularly relevant in the built environment, where high energy savings can be achieved [2]. However, there are still a number of challenges that need to be addressed due to the low effectiveness of existing practices, as they used to underexploit the interactions among buildings, trade-offs or synergies. Apart from the issue of considering the buildings as part of a more complex system, there is a challenge on evaluating the parameters related to energy efficiency or sustainability, which are usually too focused on a very specific aspect such as \"energy consumption\" and ignore other relevant parameters and impacts [3]. This evaluation, which is carried out through the use of simulation tools, results in different levels of accuracy but generally \"imply the generation of ad hoc simulation models\" [4]. This process is always prone to human error--not only when creating the simulation models, but also when incorporating energy conservation measures. Due to the complexity of the problem and as this process is tedious and consumes a lot of time, usually a reduced set of technologies is considered, \"hindering the possibility to find an optimal retrofitting solution\" [5]. Furthermore, the construction sector is slowly turning into a new paradigm of more collaborative approaches for the stakeholders, as building information modelling (BIM) [6] and integrated project delivery (IPD) [7] aiming at creating better mechanisms for information exchange and interaction and, on top of this, delivering more effective processes while reducing costs. In this context, the objective of the platform developed is to offer a collaborative solution \"for the energy-efficient retrofitting at district scale\" [8], integrating the following elements to address the problems described above:  
* **Assessment at district scale**: the tool considers the interaction among buildings and analysis the potential existing when considering the district as a whole and analyses the inter-building interaction both in terms of passive and active relationships. This is done through the implementation of tools that can enrich the models through adding the shadows that affect the buildings under study [9] in order to perform an appropriate evaluation at district level. At the same time, technologies are proposed at district level, exploiting the synergies among buildings in terms of sharing energy systems and energy production [10]. * **Use of Multiple-Criteria Decision Analysis**: the evaluation framework is based on evaluating the performance of the candidate scenarios against a set of criteria in different fields, offering a more comprehensive evaluation and more informed decision making. * **Energy Conservation Measures (ECMs) catalogue**: the tool provides a wide catalogue of existing technologies that can be implemented at different scales (zone, building, district) and different fields (passive, active, RES or control). * **Use of standards**: use of standard file formats for building definition (Industry Foundation Classes, IFC) [11], and district scale (CityGML) [12], to ensure the implementation of a collaborative approach and interoperability among the different components and tools. * **Interoperability**: the use of standards and the generation of a District Data Model ensure the interoperability among the tools that have been integrated for the processes of generating, evaluating and optimising the candidate retrofitting scenarios. * **Use of Integrated Project Delivery (IPD)**: the tool fosters the implementation of more collaborative approaches as IPD towards ensuring more informed decisions and improved processes compared to business-as-usual [7].