Emanuele Storti

Emanuele Storti's picture
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Professional title: 
Organisation name: 
Daisy lab, Marche Polytechnic University
Organisation type: 
Early Adopters Selection Criteria: 
Multidisciplinary NGI researchers in ICT, social sciences & humanities
Innovation platforms & IT clusters
Which of the following NGI values are you championing?: 
Human-centric. Citizen co-design. Participatory. Communities using environmentally-friendly and sustainable resources, e.g. energy
Interoperability and standardisation. Interoperability testing. Key enabling technologies: 5G, IoT, cloud, big data, cyber security
New applications and services across industry verticals and public sector. Socio-economic impacts

Early Adopters

Short Description: 

The Daisy Lab at Marche Polytechnic University (http://www.univpm.it) focuses on the usage of collaborative and semantic technologies, Big Data, Machine Learning and AI to support and empower communities of citizens and organizations. Among our recent projects:

- Analytics for Citizens. A growing number of public institutions all over the world are making data available in open formats, thus enhancing transparency and accountability, stimulating innovation, and promoting civic awareness and engagement. However, fragmentation and heterogeneity of datasets and lack of common standards ask a consistent integration effort to actually access and use data. By relying on knowledge representation and automated reasoning we provide services to enable communities of citizens to easily access, mash-up and compare open data available on the Web. Users can collaboratively create libraries of custom metrics for any relevant topic (environment, spending, pollution, energy, traffic), review and share them, use them to annotate and make sense of open datasets. For instance, a user can compare open data on housing prices of two cities with their crime rates through her own user-defined metrics.

- Innovation support for Virtual Organizations. A semantic platform for a network of collaborating organizations, with the purpose to support innovation processes by identifying relevant internal and external knowledge according to an Open Innovation approach, enabling integrated network-level monitoring and comparison, detecting bottlenecks and pitfalls for continuous improvement. It is realized through a semantic framework enabling storage, integration and analysis of heterogeneous (Big) Data produced by an ecosystem of cooperating organizations, collaborative tools and AI technologies.

The research group offers courses, seminars, consulting on Information and Knowledge Systems, Big Data architectures, Data Science and Machine Learning.

NGI solution(s) used by your organisation: 

We rely on Big Data architectures, semantic technologies to represent, make sense and share information and knowledge on the Web, Artificial Intelligence for automated reasoning and collaborative technologies to promote cooperation and interaction within communities of citizens and organizations.




Member for
5 years 2 months