As we indicated in our previous post, our team is growing, increasing our skills to make GeoDB a solution that works not only on paper, but in the real world. In GeoDB we’re building a protocol for big data analytics supported by DLT, rewarding users for providing their information and providing a public analysis framework with accurate information.
We want to build GeoDB using several DLT technologies that are a reality, and our team is currently analyzing and testing multiple solutions, from public infrastructures such as Ethetreum and IOTA, to corporate solutions such as Hyperledger in several of its flavors and other tools such as IPFS, FileCoin, POA and a long etcetera. Our goal isn’t to create an infraestructure from scratch, but to interconnect several components to facilitate the most appropriate solution for our purpose.
While the above frees us from a lot of work, the interconnection of a wide range of technologies to generate an infrastructure is not a trivial work, and our team must solve several challenges to make GeoDB a reality. We’re not going to make a compendium of these challenges here, but to highlight a specific one, those of you with technical background in DLT will know that providing a DLT infrastructure with the necessary scalability, privacy and security to support analytics from a big data perspective is not an easy task, and one of our newest team members, Álvaro García, is working hard to help us refine our proposal in this area.
We copy below a fragment of his biography so you know him and we invite you to visit his personal page, https://algarecu.wordpress.com/, to know him better.
Álvaro García-Recuero holds a Ph.D. in Computer Science by Université de Rennes 1 (UR1), developed at the French National Research Institute of Informatics and Automatics (INRIA) in Rennes, Brittany, France. Since May 2017, he is graduated with a PhD dissertation titled “Discouraging Abusive Behaviour in Privacy-Preserving Decentralised Online Social Networks” at Inria Rennes (Brittany) by the University of Rennes 1. His Ph.D. dissertation proposes a privacy-preserving design of a protocol for abuse detection over the Internet, namely dPSI (decentralised Private Set Intersection), while Data Minimisation is employed for achieving reduced protocol runtime in future decentralised deployments. He has also built and hacks on Trollslayer, a platform for crowdsourcing, characterisation and victim-centric abuse detection in Online Social Networks. He releases his research contributions as Free Open Software on his github, thus supporting free software and reproducible scientific research. He is always interested in bold, challenging ideas that push-forward Research & Innovation.
We believe that the above makes clear his capabilities, so we’re delighted to have him on our team.
Until next time ;)