Data quality and data limitations: working towards equality through data curation
The 16th edition of the International Digital Curation Conference (IDCC21) will take place on 19th of April 2021 at the Edinburgh International Conference Centre, Edinburgh, UK. At the moment this event is planned a hybrid conference. IDCC21 will take place as a co-located event to RDA's 17th Plenary.
The 16th edition of IDCC will focus on data quality and its impact on research output. Suggested topics include transparency in all aspects of data collection and assessment, data sovereignty, promoting diversity and inclusion in digital skills programmes, and the curation of misinformation.
If conditions permit, we hope IDCC21 will be a hybrid event, allowing people to take person both in person and remotely. The virtual aspect of the event should enable us to open the conference to a broader audience.
The programme will be condensed to one day as opposed to the customary two days. The main Programme will take place on Monday the 19th of April and will consist of keynote lectures, papers and lightning talks. We will also be hosting the IDCC Unconference on Tuesday, 20th of April. A draft programme will be available soon.
IDCC21 will run in parallel with the RDA 17th Plenary Meeting, which will take place 20-22 April. The RDA Plenary is hosted by the Digital Curation Centre, as part of an Edinburgh week of data management. The RDA Plenary will focus on global challenges for opening and sharing data.
You are invited to submit proposals for papers, lightning talks and posters. You are also invited to submit topics for discussion at the Unconference.
Given the shorter time period and uncertainties over the conference format, we will not be inviting submissions for demonstrations and workshops.
Call for Papers
The key question we wish to ask at IDCC21 is:
How can we ensure data collection and curation works for society at large?
Papers are invited, but not limited to, address one or multiple themes in the broad scope of data quality and data limitations:
- Documenting and avoiding biases in datasets (e.g. clinical trials, facial recognition training datasets, machine learning).
- Anticipating use, avoiding misuse: communicating the applicability or otherwise of data to research questions.
- Non-custodial archiving, "documenting the now", and strengthening the archives of marginalized communities.
- Curating propaganda, misinformation, disinformation and falsified data. How do we protect the integrity of research data?
- Research data and curation in the contexts of geopolitics and "data nationalism".
- Data documentation for FAIRness and data quality.
- Applying data ethics in curation and assessment of data quality.
- Developing digital skills programmes to promote diversity and inclusiveness in the data science and curation professions.
- Indigenous data sovereignty, community archives and application of the CARE principles.
- Addressing inequality: broadening the benefits of data-driven science to more and diverse stakeholders.