Because good research needs good data

Call for Papers

‘Visible data, invisible infrastructure’

Research data management, and digital curation generally, is becoming a mainstream academic activity. Universities and research institutions are ramping up support and infrastructural provision for it. Funding bodies are strengthening their requirements for it. Visionary researchers and practitioners are tackling the remaining barriers.

The success of this transition might be measured in two ways. First, is data recognised as a valuable scholarly output, enjoying the same visibility and prestige afforded to journal papers? Second, is the digital curation infrastructure so well embedded and supported that everyone can use it without a second thought?

The IDCC16 Programme Committee invites submissions to the 11th International Digital Curation Conference that contribute to the discussion of visible data and invisible infrastructure. One strand will cover organisational strategies and technical developments that promote data availability, discoverability, and reusability. The second will focus on embedding support, integrating services and aligning with researchers’ workflows.

Proposers should identify the session theme they most closely align with and submit using the templates provided on the Submissions page.

Session themes

Visible Data

Data sharing

Submissions should describe initiatives to support data sharing and enhance discoverability. These could describe infrastructure and tools, or initiatives to encourage cultural change and promote uptake:

  • understanding data sharing practices
  • data publication
  • visualising data and its connections
  • discovery metadata, data description, data access statements
  • persistent identifiers, data citation and linking mechanisms
  • data catalogues, indexes, registries – new developments and use cases
  • data indexing
  • ethical issues

Data reuse

Submissions should tackle issues associated with supporting reuse. These could consider what is required from data producers and data consumers to make reuse feasible, or how this might be encouraged:

  • understanding data reuse practices
  • making data fit for a given reuse case
  • building reuse into researchers’ workflows and culture
  • finding new patterns in data, facilitating novel applications
  • facilitating the reuse of sensitive, safeguarded and controlled data
  • the role of the library in supporting researchers to find, acquire and reuse data
  • reusing data involving human subjects
  • transnational issues with clinical trials across countries

Recognition and reward

Submissions should address organisational and disciplinary strategies to encourage a culture of data management, sharing and reuse.

  • recognising data value, adding value
  • peer reviewing data and data management plans
  • trusted repository certification – experiences and further needs
  • tracking impact and reuse by traditional or alternative metrics
  • incentivising research data management, sharing and reuse – for example, through research assessment
  • funder and publisher data sharing policies – influencing, compliance

Reproducibility, Transparency and Trust

Submissions should explore issues concerned with reproducibility, transparency and trust associated with open science:

  • critical perspectives through the lens of the research life-cycle
  • models, terminology and taxonomies relating to these concepts
  • qualitative and quantitative assessments of community practice
  • service implications for data stakeholders including researchers, publishers and libraries

Invisible infrastructure

Curation infrastructure

Submissions should describe services or infrastructure to support digital curation and research data management. Emphasis should be placed on how these align with user workflows and needs so as to become taken for granted and thus ‘invisible’:

  • delivering curation services – reflections, evaluations, usability studies
  • team science – data management to support collaborative research across boundaries
  • novel applications of metadata, linked open data, and research object standards
  • pervasive interoperability in curation environments, ‘data fabrics’
  • embedding sheer curation into data workflows
  • building legal compliance into infrastructure – for example, EU data privacy regulations
  • RDM processes and operational practices to ensure data integrity

Education and training

Submissions should explore the education and training needs of data curators, researchers or the staff that support them:

  • best practice in curriculum development and course delivery
  • equipping researchers and librarians with data skills – data and software carpentry
  • using datasets in a learning and teaching context
  • establishing career profiles and trajectories that value and reward curation skills
  • building ethics into the human curation infrastructure

Sustainability and strategy

Submissions should consider how digital curation and research data management activities can be sustained and developed in the medium to long term:

  • cost and funding models
  • cost–benefit analyses, return on investment calculations
  • business cases, strategy, planning
  • data management as institutional risk management
  • sustaining shared services – moving across the collaborative continuum
  • evaluating and harmonising national data policies to keep them relevant
  • strategies and policies for ensuring trustworthiness of data