Speaker
Description
Border regions, often characterized by unique socio-economic dynamics and shared governance challenges, require robust data management systems to foster cross-border collaboration and sustainable development. This research investigates the purpose and implementation of data management practices in border regions of different countries, focusing on their potential to address cross-border challenges and leverage opportunities for growth.
The study adopts a mixed-method approach, combining qualitative analysis of governance frameworks with quantitative assessment of spatial, demographic, and socio-economic datasets from selected border regions. Key objectives include identifying barriers to data sharing, understanding the impact of legal and technical discrepancies, and exploring innovative solutions to enhance data interoperability and standardization.
Principal results reveal significant challenges in data management stemming from disparities in legal systems, technological infrastructure, and data governance policies. These factors hinder efficient data sharing and joint decision-making among cross-border stakeholders. However, case studies demonstrate that emerging technologies, such as geographic information systems, blockchain, and big data analytics, can bridge these gaps by enabling integrated data platforms. Stakeholder engagement and capacity-building initiatives were found to play a crucial role in overcoming institutional and technical barriers.
Analysis of recent research underscores the relevance of data management to cross-border governance. Xue et al. (2024) emphasize the importance of cross-border interactions in advancing sustainable development, highlighting the role of collaborative data management in achieving global sustainability goals. Krüger et al. (2024) propose a framework for cross-border governance, identifying critical factors such as institutional alignment and shared data systems, which support this research’s focus on governance improvement. Kurowska-Pysz et al. (2018) examine sustainable planning strategies for cross-border cooperation, advocating for enhanced spatial data integration and collaboration between border cities. Leibenath (2008) offers theoretical insights into the gaps in cross-border governance and spatial development, underscoring the need for robust data-sharing protocols and interoperable technologies to bridge these divides.
The research concludes that effective data management in border regions not only facilitates sustainable development but also strengthens governance by enabling informed policymaking, efficient resource allocation, and enhanced social cohesion. Recommendations include the development of standardized data-sharing protocols, investment in interoperable technologies, and the establishment of cross-border data governance frameworks. These measures are essential for transforming data into a strategic asset for border region development and integration.
References
1.Xue, S., Xiao, H., & Ren, J. (2024). Cross-border interactions on the sustainable development between global countries. Resources, Conservation and Recycling, 204, 107525. https://doi.org/10.1016/j.resconrec.2024.107525
2.Krüger, C., Pennabel, A. F., Paschoalotto, M. A. C., Guimarães, F. H. C. B., Medeiros Kruger, N. R., Meneguzzo, M., & Ferreira Caldana, A. C. (2024). Framework for cross-border governance: from cross-border critical factors to sustainable development. Public Management Review, 1–62. https://doi.org/10.1080/14719037.2024.2443061
3.Kurowska-Pysz, J., Castanho, R. A., & Loures, L. (2018). Sustainable planning of cross-border cooperation: A strategy for alliances in border cities. Sustainability, 10(5), 1416. https://doi.org/10.3390/su10051416
4.Leibenath, M. (2008). Exploring the gaps. In: Cross-border Governance and Sustainable Spatial Development. Central and Eastern European Development Studies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79244-4_1
| Keywords | border regions; data management; cross-border collaboration; governance; |
|---|---|
| Best Congress Paper Award | No |
