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Data Science Journal – Scope

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CODATA Data Science Journal Scope

The scope of the Data Science Journal includes the following:


  • Data capture, generation, monitoring, synthesis, analysis, evaluation; metadata;
  • Data structures; data storage, indexing, retrieval;
  • Data exchange, sharing;
  • Data display and manipulation;
  • Data dissemination strategies; printing, CD-ROM, internet;
  • Data quality, data consistency, data complexity, data standards;
  • Data uncertainty and decision making; security;
  • Data stewardship, data curation and data preservation;
  • Data dissemination, discovery, repurposing;
  • Data service; data and society;
  • Data policy;
  • Data capacity building (i.e. training in effective standard- based data management, documentation, and preservation; emerging field of data science etc.)


  • Database planning, design, maintenance; archiving;
  • Interfacing databases to the internet; to other systems, to data products; interoperability;
  • Database standards; compatibility; federated databases;
  • Data mining, knowledge discovery;
  • Human-computer interfaces; visualization in databases;
  • Use of database packages, commercial issues; distributed databases;
  • Legal issues, intellectual property rights; data access;
  • Financial management, pricing, marketing, licensing; e-commerce;

Processing, Complexity, Scalability, Distribution, Interaction

  • Active distributed systems, sensor swarms, data streaming;
  • Performance issues, scalability, requirement engineering;
  • Web service technology;
  • Cloud Computing;
  • Actor-centric/ decision-support systems;


  • Industrial applications, industrial requirements;
  • Adding intelligence to data systems, data modelling;
  • Novel applications; case studies (new and established data analysis and management practices); interdisciplinary systems;
  • Mission-oriented data activities of global features, e.g., global warming and sustainability, or disaster avoidance, mitigation, or response;
  • Human-centric data activities, e.g., health, safety, security;
  • Cultural heritage;
  • Crisis Information and disaster management support;
  • Data management for policy development;

Interfaces with Experiments, Models and Information Complexes in the Internet

  • Online simulations, databases; virtual laboratories;
  • Video-articles, tangible presentations, virtual reality in databases;
  • Interplay of data and models;

Editorials, Essays and New Perspectives on Data Activities

Other: We also intend to include book reviews and conference proceedings. In the future, we might include a commentary function to allow readers to comment on papers.