Martin Serrano

From 05/06/2023 to 31/12/2023

Paired Teams

[C-BRIDGE]: EU-USA collaboration for Business Research, Incubation and the Development of Goals, Entrepreneurship and adoption of activities promoting the creation of Standards in the next generation of smart cities and services

National Institute for Standards and Technology

Dr. Martin Serrano is a Senior Research Fellow in the Insight Centre for Data Analytics at the University of Galway. Dr. Serrano is a recognised expert in Semantic Interoperability and Distributed Systems by his numerous scientific contribution(s) using Liked Data and Semantic Technologies for the Internet of Things and thus store collected sensor’s data in the Cloud. He is also an innovator by his work on defining the Data Interplay in Edge Computing using the Linked Data paradigm, He has also formalised the use of Statistical Methods for measuring Data Density in Complex environments like Smart Cities and systems automatization and Published the NIST H-KPI Framework, in those works he has got best innovation awards for his scientific publications and high impact contributions.

EU-USA C-BRIDGE project’s main objective is to define a set of collaborative activities to assist on defining best practices for Business Research, Incubation practices and the Development of business Goals to identify principles for Entrepreneurship activities [C-BRIDGE] and for the identification and adoption of market-related activities validating the methodology in the next generation of smart cities & services. The applicability for C-BRIDGE shall be domain agnostic and independent of the domain area where this can be used as far as the purpose is helping to transform scientific knowledge into community impact(s) directing market opportunities. In the context of C-BRIDGE, the smart cities application domain area is selected with the main purpose to promote and demonstrate the adoption of the holistic methods (a knowledge-based framework) in next-generation smart city services. In this context the aim of C-BRIDGE is to validate and promote a standard methodology to self-assess smart city maturity with the objective to validate and demonstrate its application for data-driven innovation and the use of smart city data being used as empirical experience for commercial value.

C-BRIDGE method addresses the need for a new approach for data innovation. In the other hand the maturity assessment of a smart city based on the technology that is deployed, the number of services that are provided and/or the data that is generated directly from the city infrastructure is today one of the most challenging activities; mainly because the complexity that exist when connecting all the different aspects of the data and also because this process requires the understanding and participation of all the systems and stakeholders involved in the production of the data. This process taken as example is called data continuum and it is also a main outcome in C-BRIDGE. Data Continuum is supported from the need that data systems collaboration requires that aspects about data that want to be share can be understood across the systems and that new ways for data management (big data) can be deployed and implemented efficiently. Beyond this challenge the quantification of the data that is produced in a smart city is a progression in the state of the art and represent multiple opportunities about explaining why the data needs to be shared and also the opportunity of the data to be used.

The Next Generation of services and applications using the Internet should support large amounts of distributed data to facilitate not only big data production, processing and storage but also accountability and resilience of the data to the different systems that will make use of the data; the current problem resides in the methods to classify, identify, access and share the data and still not less important the methods to define the cost from the use of the systems data and identify who pay for those management and other services (i.e. data quality, evaluation, measuring, etc.) that can derivate from the use of the smart city systems data.

C-BRIDGE project is a EU-USA collaboration project that investigates and defines a methodology to transform scientific knowledge into community impact(s) and motivating scientific communities to direct results towards market opportunities.

The data continuum is the process that modern data systems use for data production and collection and is an inherent characteristic of any information system today. In the other hand the analysis and the capability to map data to other pieces and/or even establish relationship amongst the different parts of the data is not a trivial task. Data aggregation and data mapping are the two main functions that makes the data meaningful. The trend is that everybody will continue producing data and especially with the emerging of human-centric applications and services this trend will grow. Big data paradigm has facilitated that data sets and data bases systems can evolve being able to process large amounts of data, at the same time that information systems have also evolved establishing stream processing methods. In the IoT and particularly from a sensor networks perspective the connectivity is the main element to be able to produce large amounts of data, from an applications system perspective the data aggregation is the main element that allows the delivery of large end user datadriven services and that enables analytics capacities to better understand and make use of large amount of information.

The Definition and/or Identification of the experimental and innovative goals for entrepreneurship using the C-BRIDGE methodology is underlined as main asset and the entrepreneurship methods studied and the experience used as adoption to perform innovation activities of engagement towards community impact are demonstrated to be part of the success of the C-BRIDGE methodology.

The C-BRIDGE project focuses on studying common practices for data monetization data-driven business development and data cost model entrepreneurship, several activities have been investigated and some other performed accordingly to the C-BRIDGE proposed plan, the following results can shortly summarise the C-BRIDGE methodology.

Starting from the expected impact described in the application form, and finishing with the latest activities and plans from the EU-USA C-BRIDGE project activities the following list is a comprehensive list of impacts generated during the three months period report:

Development/advancement of innovative technologies

The EU-USA C-BRIDGE project proposes business research, incubation and development of goals, entrepreneurship and adoption activities as part of the C-BRIDGE methodology. The C-Bridge methodology aims mainly to advance the state of the art in business planning/incubation and exploitation of the smart city maturity assessment and the cost model by means of the data produced by the city systems data. The C-BRIDGE method has been described and proposed at NIST as best practices for incubating ideas and transfer this into actionable and innovative products.

Sound Scientific Validation

The use of C-BRIDGE methodology in practical and realistic scenarios in the context of smart city maturity assessment and data management systems process. At C-BRIDGE we aspire that the methodology acts as an accelerator about innovation and incubation aspects organising the process how ideas, developments and technologies are aligned to progress and produce scientific value and can be used to attract interest make a useful commercial model for impact in society, i.e. for example promote digital transformation using the C-BRIDGE method.

Advancing standards

Currently there is a lack of a similar Innovation Methodology that needs in one hand the principles to innovate and define the commercial value of the data and in the other hand has the EU-USA international level, thus C-BRIDGE offers a unique environment for us to test C-BRIDGE usability and validate this in multiple smart city systems with the idea to be large adopted and thus promote the creation of a standard method, this is in the framework of the published and already available H-KPI framework. Thus advancing the creation of standards.

Strengthening research collaboration with the US/Canada

The increased level of top research from both partners in the team, participating in the C-BRIDGE activities enhanced already the vision towards what is achievable to innovate in the context of Data Interoperability, introducing the new parading of data continuum, as a scientific idea and transform it
into a near to industrial product with commercial value implementing and deploying the data continuum in the context of smart city applications.

Strengthening innovation collaboration with the US/Canada

The C-BRIDGE is working towards speeding up developments in the existing activities for smart city self-assessment and will leave the process as the legacy to any other individual or organisation that want to benefit from transforming knowledge into commercial value.

Building solid connections and partnerships in Europe and in the US/Canada

The C-BRIDGE methodology is successfully designed and conceptualised in the context of the NGI Enrichers collaboration, previously the NGI H-KPI Framework is already published as NIST technical report which received the Best NGI Explorer Award for its impact and results, C-BRIDGE will focus on maturing this reference framework and set the preparative to innovate and look at enhancing knowledge-sharing and establishing-consolidate the long-term collaborations by using these achievements and the results form EU-USA C-BRIDGE project, demonstrating that advancing on NGI technologies, services, standards and also look at the commercial opportunities is possible.

Accelerated contacts/engagements with R&D partners for future collaborations

It usually takes a huge amount of effort to deploy a robust large scale deployment to show full scalable functionalities. C-BRIDGE is looking at possibilities to deploy / build a testbed-like demonstrator, following C-BRDIGE steps, with the objective to facilitate the innovation and entrepreneur practices, i.e. rapid prototyping that C-BRIDGE experiments and efforts can reduce considerably the learning time and thus guarantee execute the activities as proposed. There is currently an opportunity to further collaborate with John Hopkins University JHU in in the area of smart cities innovation, to define an innovative solution to data management problems and thus C-BRIDGE methods and H-KPI explorer framework are used as baseline.

Expanding collaboration within the NGI community

The fast development with open source software technology, and the tendency to adopt the Open Source / Open Data paradigms as a standard way to start working in a community and achieve more in community than isolated demonstrated in recent years, even large corporates like Microsoft has join the race to work on the open source space to have more trustable, resilient and most important adopted by the community software products. There is currently a discussion for defining a project opportunity with FIWARE foundation and thus further collaborate in the development of standards in the area of data management and software data systems, the project idea aspire to define an innovative solution to data management problems where C-BRIDGE methodology is the baseline.

Paper submission for further publication – indicate, only EU author(s), or jointly with the host
organisation

An ongoing publication that will contain the formulation of the Internet of Things Science Evolution approach, a design paradigm designed and discussed withing the C-BRIDGE project, also including the IoT Data-Cloud Stack Update, the innovative first of a kind Data Continuum and its applicability in Future Networks that summarised the initial study of common practices for data monetization datadriven business development and data cost model entrepreneurship is in progress. This publication will be submitted in a top international conference for evaluation and if accepted the design principles, the study results and the EU-USA C-BRIDGE methodology will be presented.

Conference attendance with paper/poster/ proceedings

The first event and public engagement activity was with the IEEE SIGCOMM community, an event organised in Columbia University, NYC, USA as a workshop and where the C-BRDIGE methodology and findings on data continuum were presented and discussed. Dr. Martin Serrano was invited as keynote speaker presenting the C-BRIDGE project progress and design principles for the methodology.

Conclusion

This Mid-term public report summarises the progress of the EU-USA C-BRIDGE Project, it addresses the reviewed C-BRIDGE methodology and extended the proposed IoT Cloud-Data Stack and also presented the design principles for the Data Continuum enabling Data Exchange, and Semantic Interoperability
with Trust in Future Networks. The design principles from the C-BRIDGE methodology as steps for innovation and commercial value are proposed and presented in this report as part of the foundations for the Internet of Things Science, a way to demonstrate the applicability and feasibility in using the C-BRIDGE methodology as best practices for innovation, Internet of Things Science describes the challenges for AI-powered applications and the use of trusted data-centric sharing and interoperability services and applications in future networks.

References

[1] Kanza Sohail, Maksim Belitski, Liza Castro Christiansen, “Developing business incubation process frameworks: A systematic literature review”.
Journal of Business Research, Volume 162, 2023, 113902, ISSN 0148-2963, https://doi.org/10.1016/j.jbusres.2023.113902.
https://www.sciencedirect.com/science/article/pii/S0148296323002606

[2] S. Sreejesh “Business Research Process”, 2014 https://zamaros.net/Business%20Research.pdf

[3] UCI Libraries, “Research methods for Entrepreneurship”

[4] Upakar Bhandari and Kantilata Thapa “Research Review on Adoption Process”, June 2018
DOI:10.13140/RG.2.2.19255.21920
https://www.researchgate.net/publication/325997102_Research_Review_on_Adoption_Process

[5] “How to build engagement in research”.
https://elearningindustry.com/how-to-build-engagement-in-research