Because good research needs good data

Call for Papers

Upstream, Downstream: embedding digital curation in workflows for data science, scholarship and society


Digital curation involves maintaining, preserving and adding value to digital content. While definitions of curation have changed little, its scope is becoming ever more pervasive. Data science is gaining prominence as a means to address grand challenges in research and society. Research and scholarship are becoming further mechanised. Public infrastructures for data storage, sharing and publishing gain further capability, while large scale mergers, takeovers and acquisitions have shaken up the research publishing sector. For policy makers, the question of how to ensure research data is findable, accessible, interoperable and reusable (FAIR) is tied to the question of how to ensure flexible and resilient infrastructures are openly available to support communities in that endeavour.

Despite their widespread applicability, digital curation skills, tools and services have a very mixed range of maturity and capability. Many organisations are only experimenting while in others they are embedded in organizational workflows. Research and cultural institutions and individual scientists and scholars have a much larger choice of technologies to help them manage research data and other digital objects of social or cultural value. Organisations face the challenge of orchestrating different on-site and off-site data services throughout the research lifecycle.  How are organisations integrating cloud services for research data into their workflows? How are embedded research practices changing to deal with data management, preservation and publishing? What tools or models help organisations to deliver more agile services to support curation? The IDCC17 organizing committee is now inviting submissions addressing these questions, including but not limited to the topics suggested below.

Suggested topics

Policy harmonisation and monitoring for a joined-up data world

  • Governance principles for curating data as a public good
  • Data management and stewardship planning; from compliance to ‘active DMPs’
  • Measuring open data compliance: what metrics, and for what outputs? 
  • Addressing copyright challenges for text and data mining
  • Evaluating data policy: is it delivering the outcomes we want?

Capacity development for open science skills and readiness

  • Competence and capability models for open science and data science
  • Curriculum development and training initiatives to bridge the data and domain skills gap
  • Recognising data and software skills in academic and professional career development
  • Exchanging good practice across professional networks for librarians, archivists, data managers and other curation professionals

Reproducibility and provenance across research workflows

  • Joining up workflows and practices across tools and platforms  
  • Applying practical policies to automate curation workflows
  • Orchestrating research data support services from multiple providers
  • Standards to enable platform integration on a one-to-many and many-to-many scale

Sensitivity, ethical data management

  • Managing de-identified data from analysis to archiving 
  • Providing services for sensitive data at the institutional level
  • Ethical challenges of sensitive data in multi-disciplinary settings
  • Making sensitive data safely reusable: approaches and lessons learned

Reusability of digital collections

  • Measuring data value for scholarly, scientific, business or social benefit
  • Using citizen participation to inspire reusable digital resources
  • Challenges in constructing community data resources and reference collections
  • Generic solutions for managing disciplinary metadata

Discoverability and data publishing

  • Metadata for machine actionable service catalogues and discovery
  • Supporting users to find data from domains unfamiliar to them
  • Skills and rewards in data journals and data journalism
  • Challenges of publishing corpora in the humanities and social sciences
  • Supporting researchers on data mining and data visualization

Submissions can take a number of forms, including research papers, practice papers, posters and workshops. Papers are all considered for fee-free open-access publication in the International Journal of Digital Curation

For information about the submission process check Submissions

For information about the submission dates for IDCC17 check Dates