Grant Proposal for Research Data Management Support in Research and Academic Institutions in Ghana

Richard Bruce Lamptey

Funding Area: Capacity building / Construcción de capacidad

Problem Statement: In recent years, the volume and complexity of research data have increased significantly across various disciplines. However, many research and academic institutions face challenges in managing, storing, and preserving this valuable data. Inadequate data management practices can lead to data loss, limited data accessibility, and reduced research reproducibility. In Ghana, researchers and librarians are still learning about research data management. Although much research is being done, the data sets are mainly unavailable for reuse or verification. This has led to duplication in studies, loss of valuable data and inability to share necessary data.   Given CARLIGH this funding support, it will conduct training workshops on research data management for librarians and researchers, to build their capacities and empower them to drive research data management agendas in their institutions, to develop data sharing platforms and data management policies, and to train and support researchers.    A project team will work with institutions with Institutional Repositories (IR). A research data librarians group will be created to share experiences and develop research data management plans for their institutions.  In addition, the project will support librarians advocating for research data management services at the institutional level and discussions about institutional open access, research data management and open science policy discussions.

Proposed Activities: Data Management Policies: Develop and implement clear data management policies that outline the expectations and responsibilities of researchers regarding data organization, documentation, storage, and sharing. Data Management Planning: The training part in this project will encourage researchers to create data management plans (DMPs) at the beginning of their projects, this can help ensure that data management considerations are integrated from the outset. These plans can help identify potential challenges and solutions for data sustainability. Data Repositories: Train the selected institution to adopt the standardized metadata practices that allows for easier data discovery and reuse. Trian researchers to provide comprehensive and standardized metadata alongside their datasets enhances the sustainability of the data. Data Training and Education: The project will provide extensive training and workshops on research data integrity and preservation, data management best practices to librarians and researchers to understand the importance of sustainable data management and how to implement it effectively. Fostering a culture of data sharing and collaboration within the academic community. Collaboration between researchers, libraries, and IT departments will be encouraged for it to be instrumental in developing and maintaining sustainable data management solutions. Community of Practice will be created to regularly assesse the effectiveness of data management practices and address any identified gaps or challenges essential for continuous improvement and sustainability. Incentives such as recognition, awards, or funding opportunities will be use to motivate researchers to adhere to data management practices and policies.

Openness: DSpace as an Open Source software will be used for the research Data repository. Any research conducted out of this research will be publish in OA journal

Challenges: Data Access and Sharing: Restricted access: Sensitive or confidential data may require limited access, which can make data sharing more complex. Data ownership and intellectual property: Researchers may face difficulties when determining who owns the data and how it can be shared without violating intellectual property rights. Data Security: Cybersecurity risks: Protecting data from unauthorized access, data breaches, or cyberattacks is critical but challenging. Data backup and recovery: Ensuring data is regularly backed up and can be restored in case of data loss or system failure. Data Collection: Ensuring data integrity and quality: Researchers need to verify that the data collected is accurate, reliable, and free from errors or bias. Privacy and ethical considerations: Ensuring compliance with data protection regulations and obtaining informed consent from participants to protect their privacy. Data Organization and Storage: Finding an appropriate data management system: Selecting the right tools and infrastructure to store and organize data securely and efficiently. Data format and compatibility: Managing various data formats and ensuring compatibility with different analysis software can be challenging.

Neglectedness: No

Success: The volume of content deposited in the reposotories and continues evaluation of the activities

Total Budget: 15000

Affiliations: Consortium of Academic and Research Libraries in Ghana

LMIE Carveout: Projects designed for LMICs addressing the specific challenges faced by these countries, such as limited resources, infrastructure constraints, and socioeconomic disparities.

Team Skills: Skills: Our team possesses a diverse set of skills relevant to data management, including data analysis, data cleaning, data visualization, programming languages (Python, R, SQL), statistical modeling, and machine learning. We are also proficient in data security and privacy measures. Capacity: We have the capacity to handle large datasets and perform complex data manipulations efficiently. Our infrastructure allows us to process, store, and analyze data at scale. Knowledge: Our team has a deep understanding of various data management concepts, such as data governance, data lifecycle management, data quality assurance, metadata management, and data integration. Lived Experience: We have practical experience in working with real-world research data from different domains. This hands-on experience enables us to anticipate and address challenges that may arise during data management processes.

How Did You Hear About This Call: Word of mouth (e.g. conversations and emails from IOI staff, friends, colleagues, etc.) / Boca a boca (por ejemplo, conversaciones y correos electrónicos del personal del IOI, amigos, colegas, etc.)

Submission Number: 103