SciDataCon 2018 seeks to explore the digital frontiers of global science by bringing together research and practice papers from a wide range of perspectives. The scope is explicitly broad and inclusive, addressing all aspects of the role of data in research.

High-level themes of SciDataCon 2018:

  • The digital frontiers of global science;
  • a global and inclusive data revolution;
  • applications, progress and challenges of data intensive research;
  • data infrastructure and enabling practices for international and collaborative research.
These themes are expanded below to give an indication of the range of topics in scope.  The topics  are indicative and overlap in places: they are suggestive of scope, but do not constitute fixed ‘Strands’ for the conference.

The Digital Frontiers of Global Science 

  • Frontier issues for research in a global and digital age;
  • data priorities and challenges of major research initiatives with regional or global reach;
  • digital frontiers, data and inter-disciplinary research challenges.

A Global and Inclusive Data Revolution 

  • Institutional capacity building;
  • overcoming data poverty;
  • data, research and the Sustainable Development Goals;
  • sustainable funding for data initiatives; and
  • Open Data / Open Science in the African context.

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;
  • achievements in Data Driven Science: covering concrete achievements in data-driven science across all research areas;
  • Big Data and broad ‘diverse’ data in their implications in research projects;
  • Big Data in the scientific and commercial sectors, covering the shared data challenges of Big Data management and analysis in both the scientific and commercial sectors;
  • data issues and strategies for research projects and programmes (particularly of international, interdisciplinary and trans-disciplinary scope); this covers all areas of research, but examples include:
    • Earth observations data and the Earth’s system, including data collection, analysis and integration of Earth observations and the study of the Earth’s system;
    • data and disaster risk research: covering the collection, analysis and integration of data for disaster risk research;
    • data-driven and sustainable cities: covering the use of data for Smart Cities, sustainable and resilient urban development;
    • data and biodiversity, ecology and the human-ecosystem interface; data for health and response to infectious disease; etc
  • data availability and data quality for research;
  • disciplinary and interdisciplinary case studies of data issues, data (non-)availability, barriers and solutions; this extends 
  • 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:
  • Open research data and Open public data;
  • citizen science and crowdsourcing;
  • ethical and legal issues associated with data and research; and so on.

Open Data, Innovation, Industry and Development

Addressing the interactions between industry, innovation and Open research data and Open Data more generally.  This includes research into:
  • private sector roles and public-private partnerships;
  • examples of innovation and development based on Open Data and open research data;
  • research and data driven innovation;
  • collaborations between the research sector and commercial organisation, particular in relation to data stewardship, data analysis and data science and Open Data;
  • data for development and innovation; and so on.

Data and Cyber-Security

Addressing the challenges of cyber-security, particularly in relation to research, industry and innovation and the interface between the three.  This includes research into:
  • the limits of Open and protecting sensitive data;
  • current research into cyber-security from the perspective of research data, Open Data and government data;
  • challenges of cyber-security for data providers and research institutions; and so on.