This dissertation targets the research question: How can a human-centered open government data ecosystem be modeled to ensure that stakeholders are engaged and find data and develops the Model of Open Data Engagement (MODE), a structured, stakeholder-centered model that links engagement activities to expected outcomes.
Abstract
Governments around the world are releasing open data with the aim of stimulating innovation, driving economic development, and advancing social good. Despite significant investment in data infrastructure and technology, many open data initiatives struggle to effectively engage stakeholders or deliver on their intended outcomes. Thus, this dissertation targets the research question: How can a human-centered open government data ecosystem be modeled to ensure that stakeholders are engaged and find data? It also explores which stakeholders should be engaged and what methods are most effective in engaging them. To address the research questions, this dissertation adopts a design science methodology and develops the Model of Open Data Engagement (MODE) through iterative design and evaluation. The process began with a meta-analysis of open data literature to identify stakeholder roles and engagement mechanisms, followed by a review of existing ecosystem models. These insights informed an initial model, which was then refined through comparative analysis of four case studies: the United States, the United Arab Emirates, Sierra Leone, and the City of Los Angeles. A global survey was then conducted to test and refine the proposed model, which was further evaluated using the Indian case study. The final MODE framework presents a structured interaction between three primary stakeholder groups (i.e., data providers, data consumers, and data influencers) through specific engagement activities that are most effective for related interactions. These engagement pathways are further linked to distinct desired outcomes, achieving the tangible benefits of open data use. Theoretically, this dissertation advances open data research by providing a structured, stakeholder-centered model that links engagement activities to expected outcomes. It addresses gaps in earlier models by incorporating the interplay between stakeholder roles, motivations, and methods of engagement. Practically, the model serves as a diagnostic and design tool for governments aiming to build or strengthen open data ecosystems. By aligning engagement strategies with stakeholder needs, MODE supports more inclusive, responsive, and sustainable open data initiatives.
The results show that open data platforms are effective in enhancing transparency indicators, although this depends on other attributes, including political commitment, legal frameworks, interoperability of data, and the accessibility of data to users.
Noah Wright, Isabella Moore· International Journal of Eme...· 0 citations
Effective environmental governance rests on two things: how willing citizens are to get involved, and how much confidence they place in the bodies that make and enforce environmental rules. Community-driven science projects, more widely known as citizen science, have become a practical way of drawing ordinary people into environmental monitoring, data collection, education, and the day-to-day work of putting policy into effect. This study examined how such projects shape public trust in environmental policy, looking specifically at whether citizen monitoring builds transparency and accountability, whether it raises environmental awareness and scientific literacy, and whether it deepens community ownership and participation. A descriptive survey design was adopted, with data drawn from 384 community members involved in environmental projects through a structured five-point Likert questionnaire, analysed using descriptive statistics, Pearson correlation, and multiple regression. Transparency and accountability were found to correlate significantly and positively with public trust (r = 0.672, p < 0.05); environmental awareness and scientific literacy also had a positive influence; and together with community ownership and participation, these three factors accounted for 64.8% of the variance in public trust (R² = 0.648, F = 117.426, p < 0.05). The study concludes that community-driven science projects are a workable strategy for strengthening environmental governance through broad participation, sharper accountability, and greater public confidence, and recommends stronger government support, formal integration of citizen science into policy processes, and greater investment in community-based environmental education.Keywords: community-driven science, citizen science, environmental governance, public trust, transparency, scientific literacy, community participation
Unknown authors· International journal of re...· 0 citations
An open-access course that teaches the foundations of advocacy and organisational change to researchers, research software engineers, and research technical professionals, structured around the UNICEF five-step advocacy cycle.
K. Pringle, Lorna Smith, Erinma Ochu et al.· 0 citations
The review demonstrates that digital technologies support anticipatory governance, adaptive policy learning, accountability, and collaborative decision-making when supported by appropriate institutional conditions, and introduces the Digital Adaptive Governance Framework (DAGF), which proposes five governance pathways linking digital technology inputs to policy outcomes.
Lwando Mdleleni, B. Ngcamu· Frontiers in Climate· 0 citations
Unless the challenges of collective analytics in e-governance, including those related to data visualization, data quality, capacity building, capacity building, technological capabilities, and inter-agency communications, are recognized, the implementation of collective analytics can be challenging.
Ashutosh Prasad Maurya, Pradeep Kumar Suri· International Journal of Inf...· 0 citations
This report delineates a literature review and framework for extended community engagement with Indigenous Peoples within the landscape of biological and genomic research. The resultant framework aims to dismantle the extractive paradigms that have historically characterised scientific inquiry, when engaging with Indigenous populations. By prioritising community agency, data sovereignty, and reciprocal benefit-sharing, this framework establishes an ethical standard grounded in collaboration and mutual respect.
To ensure both theoretical depth and practical utility, the framework is supported by synthesis of academic literature and an evaluation of existing international guidelines. This is further supplemented by a portfolio of global case studies, which provide empirical validation. By examining exemplars in the field, the framework offers a bridge between theory and the effective realities of community-based research.
This approach provides researchers with an actionable methodology to align their work with the priorities and sovereignty of participating communities. Through this integration of rigorous analysis and real-world application, this review outlining best practice in community engagement aims to ensure scientific outcomes are not only valid but also ethically and culturally sustainable.
For the purposes of this review, Indigenous communities refer to Māori, First Nations, Inuit, Métis, and other Indigenous peoples who maintain distinct histories, cultures, governance systems, and rights, with this work paying particular attention to the unique frameworks relevant to research conducted in partnership with them.
R. Sterling, Rebekah Crosswell, Maui Hudson· 0 citations
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