The webinar present topics that are part of the "Disruptive Tech and Trends" track where participants will discover about how FIWARE is positioned with regards to relevant technological areas: How to build Data Spaces, as decentralized data ecosystems, using commonly agreed building blocks ensuring Data interoperability, Data Sovereignty & Trust and Data Value Creation. How Digital Twins and cloud-to-edge continuum can be implemented with FIWARE components, using the NGSI-LD standard, and present real Digital Twin use cases How to integrate robotics and automation systems in FIWARE based digital twins How data works on your business using Artificial Intelligence and Machine Learning (AI/ML) with FIWARE and data engineering tools and techniques, such as ML-OPS.

1. Put your data to work on your business using AI/ML with
FIWARE and data engineering tools and techniques.
Joaquin Salvachúa
Profesor Titular
Universidad Politécnica de Madrid
@jsalvachua @FIWARE

2. The data pyramid
Grazzini, Jacopo & Pantisano, Francesco. (2015). Guidelines for scientific evidence provision for policy support based on Big Data and open technologies. 10.2788/329540.

3. 2
• Fiware is the key element for any smart solution: to feed the
right data to the AI/ML infrastructure for it to work properly
and get the intelligence we require.
• Data in a Digital Twin representation will enable all the
advances in AI/ML to be put in production in an easy way.
• FIWARE provides all support for all life cycle: from the
implementation of data, data processing and data
marketplace can give support to a data economy in which
plug&play AI/ML and big data services can emerge.
• A true enabler for real integent that allows to obtain wisdom
for our smart solutions, in a solid and repetible way.
Vision
Place nice illustrative
photos/images here

4. https://mattturck.com/data2021/
3

5. AI / ML Data Engineering
4
https://ml-ops.org/content/crisp-ml

6. Ongoing Architecture
5

7. 6
• AI/ML Roadmap WG in place – Produce a guide
document.
• Full support for the workflow to data for AI/ML in
all life.
• Development of frameworks to integrate Context
Broker with several types of ML frameworks like
Spark, scikitlearn, Tensorflow, Beam and BentoML.
• Full support to data access control in all points of
the full process.
• AI/ML services Marketplace concept under
development within KI-Marktplatz (AI
Marketplace) and i4Trust projects.
• Cosmos seamless GE integration with Apache airflow / ML-
Flow / Prefect orchestration to better support Data engineering
process for AI/ML. Automatic connection to Openstack-
Kubernetes clusters.
• ML-OPS support tools for non experts helping on
deployments both for training and production.
• Simple Environments for non ML experts (but experts on
the domain ). Guided notebooks based.
• Data spaces plug&play integration.
• Privacy aware ML and Data Usage control.
• First Steps on Auto-ML
• Ethics and Explainable AI : Enable new fields of application
with a true Responsible Machine Learning solution.
Delivering now, moving forward
Where we are What comes next / working topics

8. Schedule
• ML-OPS vision and how to deliver ML
– Benoit Orihuela (EGM) && Joaquin Salvachua (UPM)
• Tiny-ML : Andres Muñoz (UPM)
• The need of effective data flows for Machine Learning and Deep Learning : Miguel
Gonzalez Mendoza
• Explainable-Trustworthy AI/ML : David Campo (FIWARE)
• Open Talk about the usage of ChatGPT and similar systems in the FIWARE ecosystem.
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9. http://fiware.org
Follow @FIWARE on Twitter
Sounds nice? - Contact us!
Joaquin Salvachúa
Profesor Titular
Universidad Politécnica de Madrid
@jsalvachua @FIWARE