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. He also leads the Department of Higher Education Institutions Management at Jagiellonian University and works as President of Management Board of Polish division in Public Consulting Group (PCG Holding).
Maria Rybaczewska
is an assistant professor and researcher specializing in marketing and trade, with a PhD from Lodz University of Technology. Her work focuses on consumer behavior, retail and convenience sectors, and the resilience of these markets, combining academic research with business consulting experience in Poland and internationally.
Andrzej Woniak
is Associate Dean for Development at Akademia WSB Warszawa and teaches in finance, accounting, and management programmes. His scholarly work includes research and publications in areas such as organisational decisionmaking, information systems in management and business process improvement.
Robert Seliga
holds a PhD in Economics, specializing in management, higher education marketing, and the professionalization of management in universities. He has collaborated with leading Polish institutions, including Jagiellonian University, participated in Ministry and National Science Centre-funded projects, and is a member of the PGV research network at the University of Grenoble.
