Skip to main content

Project Coordinator (EU) :

National University of Ireland Galway

Country of the EU Coordinator :


Organisation Type :


Project participants :

National University of Ireland Galway (NUIG):

Dr. Martin Serrano is a recognised Research Data Scientist with more than 15 years’ experience in industry and applied research on Semantic Interoperability and Distributed Data Systems. Dr. Serrano is a NIST International associate investigating the use of formal mathematical methods over Large Smart City Datasets.

Rishabh Chandaliya holds a master in Artificial intelligence form university of Cork in Ireland and is a PhD Student at the University of Galway based at the Insight SFI Research Centre for Data Analytics. Mr Chandaliya has exten-
sive experience designing and developing advanced applications for the Android Platform, unit-testing code for robustness, including edge cases, usability, and general reliability.

Vinoop Sanil holds a master’s in Computer Science – Data Analytics by the University of Galway, he has extensive experience in software development working for PAC Apply and EVRY India, he is currently a data engineer at the
Internet of Things, stream processing and intelligent systems of the Insight SFI research Centre for Data Analytics



Dr. David Wollman serves as Deputy Division Chief, Smart Connected Systems Division, in the Communications Technology Laboratory (CTL) at the National Institute of Standards and Technology (NIST). Before joining CTL, he
served as Deputy Director, Smart Grid and Cyber-Physical Systems Program Office in the NIST Engineering Laboratory.

Dr. Thomas Roth leads development of the technology behind the cyber-physical test bed at the National Institute of Standards and Technology as a member of its Smart Grid and Cyber-Physical Systems program office.

Michael Dunaway joined NIST on June 7, 2021 as Associate Director of Innovation in the Smart Grid and Cyber-Physical Systems Program Office and leader of NIST's Global City Teams Challenge (GCTC).

State of US partner :


Starting date :

BONSAI:cross-Border experiments for OpeN data testbedS interconnection for Atlantic Interoperability Experiment

Experiment description

Data platforms interconnection and information frameworks collaboration requires that aspects about data that want to be share can be understood and that new ways for data management can be deployed and implemented efficiently. The Next Generation Internet should support large amounts of distributed data to facilitate big data processing and storage; however the gap resides in the methods to classify, identify, access and share the data over the Internet.

As a response on this demand, EU-USA BONSAI is a collaborative cross-Border testing framework that works over large amount of open data for optimal access, using holistic methods to classify, identify and access data and utilizes its designed service data access applications towards facilitating that information frameworks and data testbeds can provide data portability and interoperability. An Holistic-KPI method was successfully developed in the context of the NGI Explorers collaboration which received the Best NGI Explorer Award for its impact and results.

Project Objectives:

Objective 1)    The correct execution and ultimate quality of the project to ensure high impact and innovation. This objective look after the project risk management, continuous monitoring to ensure success and final reporting activities.

Objective 2)    Specification of the experimental interconnected framework using CPS and holistic methods for data sharing and interoperability and its application over large heterogeneous data sources like for example Open Data. This objective includes an SoTA analysis to validate best technologies, platforms and frameworks related to the main activity proposed in addition to the NIST CPS Framework and NUIG Mashups Builder frameworks.

Objective 3)     Testing over large amount of Open Data generated from NIST CPS framework and/or other sources (e.g. smart cities data-systems) that can be processed and used by the NUIG Mashup Builder. The main proposed idea is to experiment with unified access interfaces and tools that will enable the experiments execution by using the NIST Cyber-Physical Systems (CPS) framework (more details here) and the mashup builder framework called super stream collider (described here ) and a video demonstrating how the mashup builder framework works here.

Objective 4)    Increase the level of frameworks interconnection and acceptance of Data Sharing methods for the data services and information systems in the Next Generation Internet, by using the recent investigated and released Holistic method for characterising data sets to offer data facilities for experimenters and application developers on the top of the interconnected frameworks and particularly for the use of data stream feeds for large-scale consuming applications (as experiments for optimal data access, portability and interoperability.

Overall Approach:
The EU-USA BONSAI project addressed the challenge for enabling experimentation over test- ing data frameworks and Interconnect data platforms on both sides of the Atlantic facilitating data sharing and interoperability, for this purpose the use of open data sets is crucial, not only by the accessibility for the data sets but also for the use of open data standards. The use of open data is becoming more popular and particularly in applications where information needs to be exchange and share. The EU-USA BONSAI project aim to practically execute data man- agement services and operations and thus experiment stream processing methods on col- lected open data and at the same time use the Holistic KPI methodology making data sharing and interoperability more scalable across data testbeds and frameworks as depicted in Figure 1. We focus in a particular domain where open data is very popular (i.e. smart city data sys- tems) and take the opportunity that this paradigm exist on both sides of the Atlantic.


Implementation plan :

The EU-USA BONSAI implementation plan is driven by the opportunity of having the data mashup building framework (SSC) with enhanced capacities as optimized Data Provider Sys- tem using the CPS Framework. It is planned to use large open data sets (i.e. from Smart Cities and validate the experiments). The Smart Cities and their data generation is one of the most suitable environments to test and validate our experiments. The US and EU cities and regions (Atlantic Cities) in terms of IoT technology adoption are continuously deploying technology and services which fits the scope of EU-USA BONSAI in terms of using real open produced data. Cities operate already IoT infrastructures and services that generate large amounts of data, which are however not exploited or use efficiently supporting strategic development goals.

EU-USA BONSAI experiments look at hoe to enable data frameworks for interconnection and interoperability experiments to expand and upscale their deployments towards facilitating and optimising data quantification experiments to demonstrate data sharing and Interopera- bility for the next generation Internet can be done in an effective way.

EU-USA BONSAI experiments fosters the data sharing, data interoperability and the deploy- ment of Cloud Data, from smart cities for example and by using verified Open Data Sources for optimal frameworks interconnection our experiments can be done. Accessing and classifi- cation and its application over large heterogeneous data sources (Objective 1), with particular emphasis on the deployment of scalable, innovative, interoperable CPS Framework and SSC Middleware solution that leverage multi- source data and services from existing IoT Cloud Data infrastructures and applications in Smart Cities (Objective 2), Among the main objectives of the EU-USA BONSAI is able to design and deploy validation experiments over the experi- mental platforms (Objective 3) and evaluate objectively and holistically the data mashup builder performance. Figure 2 shows the proposed tasks and overall workplan.

The EU-USA BONSAI project builds a testbed-like deployment architecture, it usually takes a huge amount of effort to deploy a robust large scale deployment to show full scalable func- tionalities. Therefore, NIST CPS framework specifications facilities that our experiments and efforts considerably reduce and thus guarantee execute our experiments as proposed (see Figure 1 representing EU-USA BONSAI experiments Vision). The highly current demand on open data architectures and specifications focus our process of designing and building our experiments as scope and objectives are clear. It is EU-USA BONSAI clear responsibility define a simple, efficient and cost-effective experiment lifecycle management for our NIST CPS framework-based experiments.

Impacts :

The EU-USA BONSAI project has executed innovative experiments that demonstrates techno- logical expertise, scientific novelty and quality results in a relevant area which is already iden- tified as crucial part of the Next Generation Internet. The series of activities has created high results and impact from expo demonstrators to critical specification improvements in the H- KPI framework. The impacts are described briefly here as namely:

Impact 1: Enhanced EU – US cooperation in NGI, including policy cooperation.
This impact event took place at the IoT WEEK Showcase, an In-Person Event where the European Commission’s NGI Initiative, coupled with the National Science Foundation’s support through a dedicated session showcasing a number of the successful EU–US projects with representatives from both the EU and US participating in the panel in an interactive format (Figure 16). NUIG as coordinator of the BONSAI project, we presented results and we took take part in an interactive Q&A session together with other projects i.e. ARES Experiment, ATLANTIC-eVISION, Integrating OpenIreland and COSMOS testbeds, Vulnerability Assessment and Robust Defenses for Optimized Attacks in Dynamic SDNs Experiment and the Secure communication based on robust 3D localization Experiment.
The BONSAI Experiments presented the Stream Platform and H-KPI analysis and the extensions to the H-KPI framework to a forum of approximately 60 attendees the panel participation and the interactions made the audience aware of the H-KPI framework extensions and the undergoing experiments alike the potential of using BONSAI approach in multiple other domains i.e. industrial manufacturing, smart cities, etc with the objective of quantify impact
and measure maturity based on data produced. BONSAI extensions look at addressing the specification of large data sets for cross-domain interconnection.

Impact 2: Reinforced collaboration and increased synergies between the Next Generation Internet and the US Internet programmes.
The EU-USA NGI Atlantic BONSAI project has established the ways to demonstrate that Cyber-Physical Systems and H-KPI framework using large amount of data are interoperable, by using the H-KPI specification BONSAI experiments and the use of data mashups address the objective of interconnecting data sets and thus together with the NIST CPS framework, the BONSAI framework using mashups builder principles facilitates the necessary validated platform interconnection of data frameworks for real data and information system(s).

The EU-USA NGI Atlantic BONSAI project has demonstrated the collaboration with the NGI Explorer team by building on top of the previous work a prototype for the BONSAI Dashboard in order to reach outstanding results and being able to demonstrate as a proof of concept that data mashups and data testbed interconnections is achievable. The reinforce collaboration between NGI programs is a great success of continuity within its purpose of bridging, expanding, and sustaining a cross-continent Research and Innovation collaboration.

This impact event took place at the Smart City Congress Barcelona, an event organised in collaboration with EU FIWARE and the EU-USA NGI Atlantic BONSAI project where the cross-domain data interconnectivity was the main topic to be presented and discussed. In the panel experts from USA and Europe presented their views and findings in relation to how smart city data have evolved and how to increase intelligence. The expert panellist (FIWARE)
will debate what is the future for smart cities and the methods to measure maturity (H-KPIs) and add more intelligence to smart (BONSAI). Conclusions and next steps were discussed.

Impact 3: Developing interoperable solutions and joint demonstrators, contributions to standards.
The EU-USA BONSAI project developed a prototype for the H-KPI explored and H-KPI Builder in the form of BONSAI Dashboard with the main objective to showcase to Governments, scientists and industry communities that it is feasible to use the H-KPI framework specification everywhere and not only in academia but also industry and also consumers on the planet’s and Europe achieving its so-called twin (green and digital) transition to a zero carbon, zero waste economy that leaves no person or place behind.

At the AIOTI signature event under the theme “New green technologies are already here to help tackle the biggest challenge of our time: climate change”(Figure 18) . It was discussed that the European Commission has long promoted digital transformation to enhance economic competitiveness, while also recognising that digitisation can contribute to sustainability goals and enable the changes needed for a just green transition and that the Commission’s twin green and digital goals are seen to complement each other well.

Insight SFI research Centre for Data Analytics participated presenting in a demo space for the “BONSAI Experiments Interconnecting NUIG-SSC and NIST-CPS Testbeds" focusing on the interconnection of data sets form different domain area, i.e. wellbeing via a cough-cough app data and the most common respiratory diseases, in other to process the results, the demo room attracted approximately 60 participants between policy makers and technologist (industry) and experts (Academia).

Impact 4: An EU-US ecosystem of top researchers, hi-tech start-ups / SMEs and Internet-related communities collaborating on the evolution of the Internet
The EU NGI Atlantic BONSAI addressed a community of smart city and in particular technical practitioners from SME and start-ups looking at the most trendy elements and innovation in the sector of using Smart City data for large data sets and cross-domain interoperability enabling AI solutions, The GreenCities: Urban intelligence and Sustainability is a place where the main technology industry and technology leaders meet with the purpose to define trends and align initiatives in relation to the urban management and future mobility.

The NGI BONSAI participation served as the channel to present and discuss the latest technological advances and news around H-KPI explorer tools and the advance testing performed in the context of the NGI Atlantic collaboration framework. A set of data-driven texted experiments with recent innovative urban data centred on people mobility was discussed. The industrial focus participation and the large engagement with smart city data eco-system as this event on 20th-21st September attracted around 250 participants from of 2900 attendees where +300 industry +70 cities +35 countries with more than +250 experts.

The EU NGI Atlantic BONSAI created a direct impact in industrial education by providing a guest lecture/tutorial to approximately 25 participants about the BONSAI Experiments and the demonstration of the experiments in the topic of data modelling, mashup stream processing and cross-domain exchange. The Lecture took place at the North-eastern
university, the prepared sillabubs was dedicated to instruct industry professionals sponsored for their employee companies (i.e. TESTA, Apple.) where they can learn more about latest advances in technology and the emergence of new scientific paradigms (EU - Insight SFI Research Centre Part) and standards (USA - NIST Part). The lecture also addressed other community challenges and the technical challenges for SMEs and start-ups looking at the trendiest elements in relation to building data mashups, data management systems and data processing and analytics, this activity was performed in San Jose - Silicon Valley North-Western Campus in Ca, USA. from 03rd-11th December 2022.

Results :

The EU-BONSAI Project have implemented a series of experiments using open data from multiple domains i.e., Smart Cities, COVID-19, Automotive Traffic Data and Cultural Events data set as part of the testing about the implementation and deployment of the BONSAI framework. Having discussed the positive impacts of the experiments in this final report, the learnings and experiments serve as blueprint experiences that from now on will provide and serve as an overview of the current state of play on mashup building technologies. The EU-BONSAI project includes findings from the research activities in relation to mashup building, large data sets integration, Data & Information management and data manipulation of how large amount of data from heterogeneous sources will become available in the next generation of internet services, such applications and services are not available today, characteristic that is not accessible/existing in today’s Internet solutions.

The EU-USA BONSAI experiments have demonstrated that vast amounts of data can be collected from type to another type and from place to another place, taking as a reference the need to combine and merge data sets the mashup builder characteristic is very relevant in the advance of cross-domain data integration.

Future Plan :

Opportunities for Data Mashup Experiments include:

Enhancing Data Services, many data service platforms have been around so long, proprietary and open platforms, however they are considered more like non-accessible platforms mainly because the data and their life cycle are proprietary and does not correspond to actual shared problems that should be solved, but particular issues in closed environments and individual applications. Smart Cities for example, there is traffic data that changes at rush hours. Parking downtown data also represent a significant problem in cities by its diversity and sparsity in large geographical locations. Mashup technology and its application in smart city data systems represent an opportunity to address these challenges and they can certainly help. Emerging technologies can utilize the merged data keep traffic flowing, Parking spot sensors identified etc., These examples only represent the impact and connected features that the smart city data controlled and activated via data mashup technologies can do to reduce time for maintenance and provide greatly improved data services.

Reduced Data Management Operating Costs, the prevention of unnecessary waste of resources used in management operations while processing data is more than just a convenience; these days with so much interest in greening the planet and save energy, having a reduced data management operating cost also saves money and reduces greenhouse gas emissions. Installing mashup builder systems reduce the amount of data systems. Multiple data formats are necessary to transform a city into a smart city, but obviously there is an initial investment in using mashup engines, but this is compensated in how the data processing capacity can be added up quickly mitigate the initial investment. Data Management operations reflect also the health of the management system, the numbers veer outside the expected range of data processing capabilities reflecting unused resources, but the mashup builder system can automatically provide real-time data to back up their decisions and compensate the use of the resources and in long term it uses will be more optimal.

Improved Data Economy and Commerce, EU-USA BONSAI project encourages cooperation between multiple data stakeholders i.e. public and private organizations to collect, analyze, and process data. Data Mashup can trigger a disruptive businesses opportunity using data collected through smart city systems and improve their offered services like understand pain points, provide mashup services and applications and better target potential customers. Other opportunities can emerge as part of the Smart Applications where data is collected automatically. In this scenario, data collection at installed downtown street corners can provide data services to help people wherever they’re trying to get information from any available sources where they different formats.

Data Equitable Access. This means many residents and visitors miss out on the benefits that the data connection and interoperability can bring, by including innovation and free-flowing communication, the economic development and educational opportunity including democratic access exist. Data access and construction of mashups can be a literal lifesaver when it is necessary to provide information to people. Making a commitment to smart technology also means creating an opportunity to ensure internet access. Other alternate and innovative technologies exist to help integrate data access in data equitable manner and because it is or difficult to reach, such feature is purely technology dependent. However, the data sharing aspect and the interoperability element creates that date become a great motivator to start providing much-needed internet access to a community.

Everything Else, the possibilities with smart data technology are nearly limitless. Sensors Data is a tremendous source from tracking a car in densely populated city to know which streets has the most pollution levels and which others have been plowed after a blizzard, from sensors to bots. Data can allow the integrity of bridges and buildings to prevent full or partial collapses. The use of smart data can free up resources and make them focus on strategic activities.

NGI related Topic :

Experimental Platform interconnections

Call Reference :


The 30-months project will push the Next Generation Internet a step further by providing cascade funding to EU-based researchers and innovators in carrying out Next Generation Internet related experiments in collaboration with US research teams.

contact action add button