Data Sources, Management, and Digital Infrastructure in Social Sciences and Management shows how to move from raw digital data to usable evidence, with practical guidance on data literacy, documentation, platforms, and workflows that support transparency and reproducibility.
Data Management and Digital Infrastructure in Social Sciences shows how to move from raw digital data to usable evidence, with practical guidance on data literacy, documentation, platforms, and workflows that support transparency and reproducibility.
Key features include:
· Strategies for working with diverse digital data sources, from social media and administrative records to geospatial and sensor data
· Data governance and research ethics, including the findable, accessible, interoperable,
and reusable (FAIR) principles, privacy, consent, and responsible reuse
· Metadata and documentation practices that keep datasets interpretable over time, including codebooks and common standards
· Clear introductions to data platforms and infrastructure, including repositories, data warehouses, data lakes, application programming interfaces (APIs), and cloud or high-performance computing (HPC)
· Step-by-step approaches to data pipelines (extract–transform load, ETL), quality assurance (QA), provenance, version control, and open science data sharing
Written for postgraduate students and early-career researchers in the social sciences and management, the volume also supports instructors and research support staff who need a grounded, course-ready guide to modern data practices, including links to evidence-based management and real-world research settings.
Introduction,
1. The Data-Driven Transformation of Research,
2. Data
Literacy and Researcher Competencies,
3. Data Governance, FAIR Principles,
and Ethics,
4. Navigating Diverse Data Sources (Surveys, Sensors, Social
Media, and Beyond),
5. Data Formats, Structures, and Metadata Standards,
6.
Data Platforms and Digital Infrastructure (APIs, Repositories, and Data
Lakes),
7. Building and Managing Data Pipelines,
8. Data Lifecycle Management
Provenance, Versioning, and Quality Assurance,
9. Data Sharing, Reuse, and
Open Science,
10. Conclusion,
11. References.
ukasz Sukowski is a professor of economic sciences and humanities specializing in higher education management, social science methodology, HRM, and organizational culture, and serves as President of WSB University.
Andrzej Woniak serves as Associate Dean for Development and lecturer at WSB University, specializing in organisational decision-making, management information systems, and business process improvement.
Robert Seliga holds a PhD in Economics, specializing in management, higher education marketing, and the professionalization of management in universities.
Marcin Lis is Vice-Rector for Student Affairs and External Relations at WSB University and holds a PhD in engineering, his research interests include quality systems, innovation project management, and integrated management systems, with a particular focus on science business collaboration and knowledge transfer.
