Open Data Management Techniques Training

This DIXONTECH course provides a complete framework for understanding and applying Open Data Management principles and technologies. It explores the processes of collecting, structuring, publishing, and analyzing open data for business, research, and public use. Participants gain practical skills to manage data transparency, data governance, interoperability, and visualization using global open data standards and digital platforms.

TRAINING TOPICS:

• Fundamentals of Open Data and Governance

• Data Collection, Structuring, and Standardization

• Open Data Platforms and Publishing Tools

• Data Quality, Security, and Interoperability

• Open Data Visualization and Policy Applications

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

By the end of this DIXONTECH training, participants will:

• Understand open data principles and frameworks

• Manage and publish open data effectively

• Apply standards for metadata and interoperability

• Ensure data quality and governance compliance

• Use visualization tools for open data insights

• Develop open data strategies for institutions

• Support transparency and evidence-based policy

TRAINING IS TAILORED TO:

This course is designed for:

• Data managers and analysts

• IT and digital transformation specialists

• Public sector professionals and policymakers

• Research and academic data officers

• Civil society and NGO data coordinators

• Data journalists and open data advocates

• Anyone working with public or institutional data

TRAINING METHODOLOGY:

DIXONTECH uses interactive sessions, hands-on exercises, and case-based learning to demonstrate open data applications. Participants use open data portals, APIs, and visualization tools to create, manage, and analyze datasets. The approach integrates real-world scenarios and collaborative exercises to ensure skill transfer in both public and private contexts.

DAY 1: Fundamentals of Open Data and Governance

• Understanding open data concepts and value

• Global open data standards and initiatives

• Legal and ethical frameworks of open data

• Open data lifecycle and key components

• Data governance and public accountability

• Benefits and challenges of open data adoption

• Case study: open government data success stories

DAY 2: Data Collection, Structuring, and Standardization

• Identifying and sourcing open datasets

• Data classification and structuring principles

• Metadata creation and schema development

• Using APIs for open data collection

• Data cleaning and transformation techniques

• Implementing interoperability standards (CSV, JSON, XML)

• Workshop: building an open dataset for publication

DAY 3: Open Data Platforms and Publishing Tools

• Introduction to open data portals (CKAN, Socrata)

• Managing datasets on open platforms

• Using open APIs and RESTful interfaces

• Cloud hosting and version control for open data

• Data access permissions and sharing strategies

• Evaluating open data maturity and readiness

• Hands-on: publishing and testing an open data portal

DAY 4: Data Quality, Security, and Interoperability

• Ensuring data quality and accuracy standards

• Data validation and verification techniques

• Managing open data security and privacy risks

• Data documentation and reproducibility practices

• Linking datasets for interoperability

• Adhering to FAIR and DCAT standards

• Group exercise: improving open data integrity

DAY 5: Open Data Visualization and Policy Applications

• Principles of data storytelling and open communication

• Visualization tools for open datasets (Tableau, Power BI, Datawrapper)

• Creating dashboards and visual stories for open data

• Policy design through open data insights

• Open innovation and data-driven public services

• Measuring impact and sustainability of open data projects

• Final project: institutional open data strategy presentation