Themes and Scope of SciDataCon 2016

SciDataCon seeks to advance the frontiers of data in research by bringing together scientific papers from a wide range of perspectives. The scope is explicitly broad and inclusive, addressing all aspects of the role of data in research.

Topics in scope for SciDataCon 2016 are listed below.  These themes are indicative and overlap in places: they are suggestive of scope, but do not constitute fixed ‘Strands’ for the conference.

Research and Data

Addressing major research questions from the perspective of data issues.  This includes research into:

  • transformations in research as a result of the data revolution;
  • Big Data and broad ‘diverse’ data in their implications in research projects;
  • data availability and data quality for research;
  • data strategies for research projects and programmes (particularly of international and trans-disciplinary scope); 
  • disciplinary and interdisciplinary case studies of data issues, data (non-)availability, barriers and solutions; 
  • data requirements for monitoring, for example in relation to the Sustainable Development Goals, the Sendai Framework and other targets; and so on.

The discussion of such data issues should relate concretely and directly to specific research questions.

Data Science and Data Analysis

Addressing the frontier scientific, technical and epistemological challenges associated with data in research.  This includes research into:

  • issues around reproducibility, statistical and technical challenges in data intensive research;
  • large-scale data analysis, data mining and visualization;
  • visualisation and data exploration or representation;
  • data science and infrastructures for Big Data;
  • Linked Open Data and semantic enrichment;
  • interoperability standards in data and metadata, including brokering and mediation;
  • data integration and analysis of diverse data sets; 
  • research software;
  • data systems architecture; and so on.

Data Stewardship

Addressing issues to advance sustainable, long-term data stewardship.  This includes research into:

  • data management and curation systems and practice;
  • advancing trustworthiness in data stewardship;
  • developing institutional, national and international data repositories and services;
  • sustainability of data infrastructure;
  • long term digital preservation;
  • data stewardship in the research lifecycle and in research infrastructures;
  • rescue of research data at risk; and so on.

Policy and Practice of Data in Research

Addressing research into data policies and practice, and the role of data in scholarly communications.  This includes research into:

  • data policy development and harmonization;
  • legal interoperability and issues around the harmonisation of rights waivers and licenses for research data;
  • data and policy for science/research;
  • assessment of the impact and economic and societal value of data;
  • costs, value proposition, business models and economics of data infrastructure;
  • mapping the limits of Open Data;
  • data publication and citation;
  • research data and scholarly communications;
  • motivations, recognitions and reward in research practice; and so on.

Education and Data

Addressing research into educational and training responses to the Data Revolution.  This includes research into:

  • capacity building and education in data science, data management and data handling;
  • workforce requirements for data science and data curation;
  • curricula and competency frameworks for data in research; and so on.

Data, Society, Ethics and Politics

Addressing research into the broader dimensions of data and data driven research in relation to society.  This includes research into:

  • private sector roles and public-private partnerships;
  • research and data driven innovation;
  • data for development;
  • Open research data and Open public data;
  • citizen science and crowdsourcing;
  • ethical and legal issues associated with data and research; and so on.