Nuria Lama

European Programmes Manager, Member of the Board of Directors of BDVA, Atos Research and Innovation

Nuria de Lama studied Telecommunications Engineering at the Polytechnic University of Madrid. She has worked more than 20 years in Research, Development and Innovation in different IT environments. After several years managing the department of International projects for an SME specialized in wireless and mobile technologies, she joined Atos in 2005, where she first led a Research Unit on Rural and Industrial development. In 2006 she was appointed Head of the Research Unit on Semantics, Software and Service Engineering (30+ people) and since 2010 she is European Programs Manager at Atos. In that position she coordinates the strategy of Atos Research and Innovation in European Programs with a special focus on ICT and is key in business development. She has managed or contributed to more than 40 innovation projects in areas like Digital Platforms, Digital Transformation, IoT and Big data applied to different sectors, notably Smart Cities and Agriculture. She was one of the founders of the Future Internet Partnership, also known as FIWARE Program, which gave birth to the FIWARE Foundation. She was also one of the founders of the Big Data Value Association (BDVA) where she was first Deputy Secretary General; since 2018 she is member of the Board of Directors. She is currently leading the Task Force on Agriculture in BDVA and is involved in relevant projects like BDVe or DataBench in the big data portfolio as well as Demeter and Open Dei in Digital Transformation.

Nuria is speaking at

Focus Track 3 - Market uptake: Bringing AI and Data Sciences to Practice
November 4, 2020
10:00 am - 1:30 pm

Speakers

Description

For many years companies have been running technical benchmarks to compare the performance of different technologies and systems. This benchmarking process provides very valuable information but in many cases, it is not correlated with the impact of the solutions at business level. This was precisely the starting point of the DataBench project, funded by the EC under the Big Data Value PPP. After three years of intensive work DataBench has created an evaluation framework that is already openly available for the community. The session will introduce the different elements of the framework, including the toolbox, the way it can be used and some concrete examples run with companies and projects that work heavily with data.

DataBench has addressed one of the major barriers to the adoption of Big Data technologies, which has to do with the ability to measure the potential benefits of using Big data technologies in different scenarios. This is not exactly about deciding between one database and another one, but about understanding what the impact of such decision with have on a business process beyond the fulfillment of a technical KPI. This session will allow participants to understand the outcomes produced by DataBench and how to use them in their context through presentations, discussion panels and demos where they will also be entitled to contribute. Attendees will get knowledge on:
  • The current landscape of Big Data and AI benchmarks
  • The DataBench framework, which includes a complete set of metrics for the assessment of Big Data technologies
  • The DataBench toolbox, a web-based tool that provides a unique environment to search, select and deploy big data benchmarking tools, giving the possibility to generate unified technical metrics and derive business KPIs
  • A comprehensive set of use cases that we have run with companies in different industrial domains and projects of the Big Data PPP to illustrate the way you can get value out of using DataBench
  • Pipelines and blueprints
The DataBench toolbox follows a platform model and provides a single place where benchmarking communities and users of such benchmarks can meet. It goes beyond any work done so far by translating major technical KPIs into business KPIs, allowing us to establish relationships between technical and business decisions. As such, the session targets a multiplicity of stakeholders: benchmark providers, companies interested in benchmarking big data, projects and members of the big data and AI communities, decision-makers of companies that are thinking about their data-driven transformation and policy makers looking for evidence-based decision-support tools.

On our side, we will bring a comprehensive set of speakers falling precisely under all those categories.

The workshop will be structured around two parts (each of them can be attended independently; like this we want to facilitate that those participants that are not available for the entire workshop, select the most interesting part for them). Attending the complete workshop is in any case recommended to take maximum advantage of the contents.

Detailed agenda

10:00-10:05 Intro. Objectives of the session (Nuria de Lama (Atos)

10:05-10:15 DataBench General Overview (Richard Stevens (IDC, DataBench coordinator)

PART I. Big Data Benchmarking landscape and Big Data Pipelines

10:15-11:15 Session 1. The current landscape of Big Data benchmarks

  • 10:15-10:25: DataBench Framework for Benchmarks, Arne J. Berre, SINTEF
  • 10:25-10:40: Benchmarking platforms and AI, Axel Ngonga, BDVA TF6 Benchmark Lead, University of Paderborn    
  • 10:40-10:55: BenchCouncil Big Data and AI Benchmarks, Wanling Gao, Chinese Academy of Sciences
  • 10:55-11:10: MLPerf AI and ABench, Rekha Singhal, Senior Scientist and Head of the Computing Systems-Software Research area at TCS
  • 11:10-11:15: Conclusion on Big Data and AI Benchmarks, Todor Ivanov, LeadConsult
11:15-12:15 Session 2. A Project perspective on Big Data and AI architectural pipelines and benchmarks
  • 11:15-11:20: Introduction to Architectural pipelines, Arne J. Berre, SINTEF
  • 11:20-11:30: I- BiDaaS - Leonidas Kallipolitis, AEGIS
  • 11:30-11:40: TBFY - Brian Elvesæter, SINTEF
  • 11:40-11:50: Track&KNow - Athanasios Koumparos, Vodafone Innovus 
  • 11:50-12:00: DataBio - Caj Södergård, VTT
  • 12:00-12:10: DeepHealth - Jon Ander Gómez Adrián, Universitat Politecnica de Valencia
  • 12:10-12:15: Conclusion on Pipelines and related benchmarks, Arne J. Berre, SINTEF

12:15-12:30 Short coffee break to relax and maybe grab a coffee

PART II. Big Data Business Framework and benchmarking tooling support

  • 12:30-13:00 Session 3. The DataBench Business framework: a compelling offering to measure the impact of Big Data Technologies
  • 12.30-12.40: The DataBench business framework, by Gabriella Cattaneo, Erica Spinoni and Chiara Francalanci
  • 12: 40-12.50: The Whirlpool use case, Pierluigi Petrali (Whirlpool)
  • 12.50-13.00:  The Fill use case, Harald Sehrschön (FILL)
13:00-13:30 Session 4. A practical journey on how to use the DataBench Toolbox 
  • 13:00-13:15 Demo of the DataBench Toolbox (Tomás Pariente, Atos)
  • 13:15-13:25 AI Observatory (Marko Grobelnik, JSI)
  • 13:25-13:30 Fostering adoption of DataBench results. Needs from the point of view of Digital Innovation Hubs (Daniel Sáez, ITI, EUHubs4Data coordinator)

13:30 Concluding Remarks and closing of the session

Application Track 3 - Data Driven AI solutions
November 5, 2020
2:00 pm - 3:30 pm

Speakers

  • Nuria Lama (Parallel session chair) European Programmes Manager, Member of the Board of Directors of BDVA, Atos Research and Innovation
  • Ana Antunes (Speaker) Agronomist, SmartRural S.L
  • Giorgio Micheletti (Speaker) Consulting Director, IDC
  • Arne Berre (Speaker) SINTEF and NorwAI
  • Ioanna Roussaki (Speaker) Assistant Professor, National Technical University of Athens
  • Panos Ilias (Speaker) IT Business Analyst - DjustConnect, ILVO
  • Sander Jenssen (Speaker) Team Lead, Wageningen Environmental Research, Team Earth informatics
  • Luisa Volpe (Speaker) Head of Policy Development, World Farmers Organisation
  • Rita Gentili (Speaker) Coldiretti

Description

The agrifood sector is one of the most important in Europe, not only because of its contribution to the economy, but also because of its relevance for rural areas, preservation of the environment or impact on citizens’ health. As many other industrial sectors, in the last years it has been increasingly adopting digital technologies. Many challenges still exist in its data-driven transformation, but it is very important that ongoing efforts are recognized and used as baseline for future developments. Large scale deployments of IoT devices have produced a vast amount of data; data models of the domain have been extended, and progress has been made in terms of data sharing and digital platforms for data integration and analytics. In addition, advances in robotics, image recognition and other disciplines are paving the way towards innovative AI-based applications.

This session will build on previous discussions about challenges but will focus specifically on creating awareness about the work done so far in data-related technologies for the agrifood domain. This concept gives us the opportunity to create links between different approaches, initiatives and projects working in the domains of big data, IoT and AI. Furthermore, we want to avoid a discussion focused exclusively in technology, as seen and “sold” by technologists. The session will give voice to the farmers and will drive a lively discussion that will undoubtedly inspire and help all the participants involved or interested in the agrifood sector.
 

General track
November 5, 2020
3:45 pm - 4:45 pm

Speakers

Description

This session is for all those who have built the Big Data community of the Big Data Value Association and the Big Data Value Public Privare Partnership during these years. Before entering into a new adventure, let’s share the best memories and experiences: EBDVF 2020 is the perfect moment to tell how the BDVA/PPP made a difference in our life, in research, in the big data environment, in Europe. EBDVF is opening the floor to all community members who want to share their personal experience and thoughts about the value of the work done in the BDVA and the PPP. A call for volunteer speakers will be launched very soon: stay tuned so you can have your say! 

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