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Innovation Value Institute
Innovation Value Institute
  • What We Do
    • Are You Ready for the AI Revolution?
    • Our Services
    • Knowledge Building
    • Success Stories
  • How We Work
    • Collaborative Research
    • Research Projects
  • Knowledge Hub
    • Our Frameworks
    • Video Library
    • IVI Publications
  • Who We Are
    • Meet Our Team
    • Our Community
  • News & Events
  • Become a Member


Contact Us
info@ivi.ie
+353 1 708 6931

This research project evaluates the near-surface air temperature over different European case studies, using Global Climate Model (GCM) projections at 9 km resolution, ERA5-Land reanalysis data, multi-station observations and bias-corrected projections. The analysis is designed to support GCM selection for regional climate applications and proceeds in three stages. First, GCM reference simulations for 1985-2014 are evaluated against ERA5-Land reanalysis at the same spatial resolution to assess large-scale temporal consistency and mean climate behaviour. Second, GCM and reanalysis temperatures are extracted at the nearest grid point to multiple observing stations and compared against monthly station observations to quantify local-scale performance and spatial representativeness. Third, bias-corrected GCM projections are evaluated over the overlapping observational period 2015-2025 to assess near-term model behaviour under future forcing. Climate model performance is measured against ERA5-Land reanalysis and observational data and is quantified using root mean square error, mean bias error, correlation and other metrics at monthly and annual timescales, complemented by seasonal diagnostics, percentile-based analyses of temperature extremes, and assessments of bias stability across sub-periods.

PhD researcher

Marina Antoniadou Marina Antoniadou
GoGreenNext

Supervisory team

Dr. Tadhg E. MacIntyre Dr. Tadhg E. MacIntyre
Associate Professor, Environmental Psychology

In partnership with

EU flag
European Commission logo
Software ecosystems have become ubiquitous for developing and delivering platform-based software products, requiring organisations to collaborate with diverse internal and external stakeholders to create and sustain ecosystem value. While stakeholder management is well established in project management and requirements engineering, existing approaches provide limited guidance for identifying, evaluating, and prioritising stakeholders within the dynamic and interdependent context of software ecosystems. This research addresses this gap by developing a reference process model for software ecosystem stakeholder management. This approach supports the selection and prioritization of stakeholders according to ecosystem strategy and organizational capacity, enabling practitioners to determine which stakeholders are relevant and when stakeholder identification is sufficient.
The proposed process model guides practitioners through a structured sequence of activities, including defining ecosystem strategy, identifying known stakeholders defining ecosystem roles, establishing stakeholder assessment criteria, defining measurable stakeholder attributes, weighting stakeholder importance, assessing stakeholders, and selecting key stakeholders. Rather than prescribing a universal definition of a key stakeholder, the model enables organisations to tailor assessment criteria to their ecosystem strategy while maintaining a systematic and repeatable decision-making process. The process is supported by practical artefacts, including stakeholder logs, role documents, and assessment templates, designed to facilitate adoption in industrial settings.
The process model was developed through design science research and informed by an extensive review of the literature together with empirical insights gathered from software ecosystem practitioners. Its design emphasises flexibility, transparency, and repeatability, allowing organisations to adapt stakeholder assessment to different platform products, ecosystem structures, and strategic objectives. By shifting the focus from stakeholder influence alone towards ecosystem roles and strategy-driven assessment, the research provides both a theoretical contribution to software ecosystem stakeholder management and a practical method that organisations can use to identify and engage the stakeholders most critical to achieving long-term ecosystem success.

PhD researcher

Stephanie Ostrowska Stephanie Ostrowska

Supervisory team

Prof. Markus Helfert Prof. Markus Helfert
IVI Director
This project is a collaboration with Age Friendly Ireland (AFI), which is a local government-led shared service that supports communities across Ireland to prepare for demographic change by promoting age-friendly environments that enable older adults to live healthy, active, and independent lives. Through collaboration with local authorities, public services, community organisations, and Older People’s Councils, AFI works to improve areas such as housing, transport, access to services, social participation, and community well-being.
The project seeks to strengthen AFI’s ability to collect, govern, analyse, and share data related to ageing and age-friendly initiatives. While AFI gathers significant amounts of information through its national and local programmes, a systematic framework for data governance, data sharing, analytics, and policy integration is currently lacking. Addressing this gap will support more effective decision-making, improve programme evaluation, and ensure that the voices and experiences of older people are reflected in policy development and service delivery.

IVI Project Team

Prof. Markus Helfert Prof. Markus Helfert
IVI Director
Dr. Claudia Roessing Dr. Claudia Roessing
Research Manager, AFI Research Unit
Caroline Creamer Caroline Creamer
Director of the International Centre for Local and Regional Development (ICLRD)
Dr. Joanna McHugh Power Dr. Joanna McHugh Power
Assistant Professor, Psychology
Alejandro Mosquera Botello Alejandro Mosquera Botello
Age Friendly Ireland
Niamh Petrie Niamh Petrie
LERO/Age Friendly Ireland

In partnership with

Lero logo

Developed in partnership between Age Friendly Ireland and the Innovation Value Institute, this research focuses on establishing a robust data-driven environment for age-friendly policymaking. The project aims to enable real-time measurement and analysis of programme activities, informing inclusive, evidence-based policymaking. Key deliverables include a comprehensive review of data-sharing practices, the co-creation of architectural models, and a scalable data governance process model designed to bridge the existing gap between data management and social policy.

PhD researcher

Alejandro Mosquera Botello Alejandro Mosquera Botello
Age Friendly Ireland

Supervisory team

Prof. Markus Helfert Prof. Markus Helfert
IVI Director

Supported by

LERO logo
As cities evolve into smart, data-driven environments, the quality of open data has become the invisible backbone of next-generation mobility systems – yet it remains critically undermined by the decentralised, ungoverned nature of modern open data ecosystems. In the absence of centralised governance, maintaining data quality across multiple publishers, federated portals, and diverse data types has become one of the most pressing and unresolved challenges in open data management. This research pioneers a first-of-its-kind socio-technical process model, powered by agentic AI, that autonomously detects, adapts to, and improves data quality across complex, multi-actor ecosystems without relying on centralised governance infrastructure. This research redefines how open data quality is understood, governed, and sustained at ecosystem scale.
A peer-reviewed paper was presented at the European Conference on Information Systems (ECIS) and the project was awarded the competitive Open Data Engagement Fund by the Irish Government under the DEPENDR Ireland initiative.

PhD researcher

Sana Kiran Sana Kiran
LERO

Supervisory team

Prof. Markus Helfert Prof. Markus Helfert
IVI Director
Prof. Brian Donnellan Prof. Brian Donnellan
Professor of Management Innovation Services

In partnership with

LERO logo

Contact Us
info@ivi.ie
+353 1 708 6931

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Maynooth University
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Co. Kildare
Ireland

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