Hi, welcome to this website! If you are reading this text, I suppose you are interested in knowing something either about me or about my work, which is good. As for the former, I'm Florian Daniel, an associate professor at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) of the Politecnico di Milano in Milan, Italy. As for the latter, my work concentrates on data science, web/service engineering, business process management, crowdsourcing and blockchain.
The purpose of this site is to allow you to get some more insight into the above and to enable myself to keep track of what's useful to remember. It's a hard endeavor, but I'll try to keep the site as updated as possible. Should you not find what you are looking for, just drop me an email and I'll try to help.
Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for Business Process Management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.
Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text, providing opinions or ideas, and similar – all tasks that computers are not good at or where they may even fail altogether. The introduction of humans into computations and/or everyday work, however, also poses critical, novel challenges in terms of quality control, as the crowd is typically composed of people with unknown and very diverse abilities, skills, interests, personal objectives and technological resources. This survey studies quality in the context of crowdsourcing along several dimensions, so as to define and characterize it and to understand the current state of the art. Specifically, this survey derives a quality model for crowdsourcing tasks, identifies the methods and techniques that can be used to assess the attributes of the model, and the actions and strategies that help prevent and mitigate quality problems. An analysis of how these features are supported by the state of the art further identifies open issues and informs an outlook on hot future research directions.