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Highlights • A tokenizable e-Participation model will develop new local engagement. • Using a "democratic token" will help governments to overcome the governance deficit. • Building a BaaS neural network within a cloud framework is a scalable and sustainable solution. • A Neural Distributed Ledger (NDL) is a step beyond developing a 3D blockchain system. • A dApp called VoteKeeper uses Smart Contracts as a block producer in a virtual token. Abstract Currently, Distributed Ledger Technologies (DLTs) and, especially, Blockchain technology represent a great opportunity for public institutions to improve citizen participation and foster democratic innovation. These technologies facilitate the simplification of processes and provide secure management of recorded data, guaranteeing the transmission and public transparency of information. Based on the combination of a Blockchain as a Service (BaaS) platform and G-Cloud solutions, our proposal consists of the design of an e-Participation model that uses a tokenizable system of the actions and processes undertaken by citizens in participatory processes providing incentives to promote greater participation in public affairs. In order to develop a sustainable, scalable and resilient e-Participation system, a new blockchain concept, which organizes the blocks as a neural system, is combined with the implementation of a virtual token to reward participants. Furthermore, this virtual token is deployed through a smart contract that the block itself produces, containing information about the transaction and all the documents involved in the process. Finally, our Neural Distributed Ledger (NDL) framework facilitates the interconnection of blockchain networks in a transparent, certified, secure, auditable, scalable and traceable way.

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Approximately 15% of the world's population have some form of disability and the majority use apps on their mobile devices to help them in their daily lives with communication, healthcare, or for entertainment purposes. It is not, however, easy for users with impairments to choose the most suitable apps since this will depend on their particular personal characteristics or circumstances in a specific context, and because such users require apps with certain accessibility features which are not always specified in the app description. In order to overcome such difficulties, it is necessary to obtain a user profile that gathers the user's personal details, abilities, disabilities, skills, and interests to facilitate selection. The basis for our research work is to develop an app that recommends a set of apps to users with disabilities. In this respect, the focus of this paper is to obtain a semantic user profile model on which more precise search requests can be performed. The disability we have chosen to concentrate on is that of visual impairment. We propose an ontology-based user profile that matches users' characteristics, disabilities, and interests, and which not only simplifies the classification process but also provides a mechanism for linking them with existing disability ontologies, assistive devices, accessibility concepts, etc. Moreover, thanks to the inclusion of semantic relations and rules, it is possible to reason and infer new information that can be used to make more personalized recommendations than a simple app store search.

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