Research Data Management and Policies

The focus of this theme is on topics related to policies, procedures and services for managing research data. What infrastructures and initiatives at different levels (local, national, international), such as frameworks, protocols and standards are needed to improve the value and benefit of data. The topic also includes items related to the provisioning of services that support good data management practices, human and organisational:

  • Research data management lifecycle related topics
  • Data Management planning and related tools
  • Roles in research data management
  • Policies for research data management

Open Data and Data Citation

Measuring the progress of the Open Data adoption and its growing impact is vital for decision-making and funding processes. Metrics that can serve as reward or penalty for data publishers for making their work understandable, accessible and reusable by the research community. These metrics will greatly help to encourage the open science movement. Successes, trials and ideas on topics such as below are all welcome:

  • Data publication and citation
  • Leveraging Open data
  • Data curation and preservation
  • Indicators and metrics for data citation
  • Making data sharable (FAIR) without compromising IP and impact

Data Privacy and Security

Researcher needs and to report on best practices and technical aspects that help new research infrastructures to ensure security, trust and confidentiality. Papers about gaps in the current services offerings, security in Big and Open Data, policy frameworks and topics on:

  • Ethics
  • Legal and regulatory
  • Policies related to privacy and security of data
  • Cybersecurity

Data science and skills

The skills as needs for researchers to be able to manage (open) data, to conduct research. These skills follow the research life cycle and cover design and setting up research data, data production, management, analysis, open access publishing and other ways to act in and beyond one’s own scholarly and disciplinary community:

  • Data Science related topics: Data mining, data fusion/integration
  • Approaches, methodologies, initiatives and needs to increase data analytic skills
  • Data management skills
  • Capabilities to build, maintain and support advanced digital services for data-driven research

Technologies for cyberinfrastructure

The focus of this theme is on the various technologies that can be used to build on cyberinfrastructure. Technologies for cyberinfrastructure relates to the distributed systems that are used to support research in data intensive environment. This can extend beyond the distributed computer systems, computer networks, information systems and communication technologies. Successful planning, development and implementation of various technologies are all welcome:

  • Data systems architecture
  • Data infrastructures
  • Federated identification and access (E.g., SAFIRE, EduGain)