Aims and scope
The Journal on Data Semantics (JoDS) is a peer-reviewed journal acting as a forum for the scientific community for the exchange of ideas concerning the foundations of modeling, the semantics, the representation, and the overall engineering of data, especially in the context of their interplay with software systems and applications built on top of them. Apart from the traditional research papers, surveys and empirical research papers are also welcome.
The main topics for the Journal on Data Semantics include, but are not limited to:
Metamodeling and design patterns
- Metamodeling and the foundations of data metamodels
- Metadata and its management
- Design patterns and design reuse for data and software models
Conceptual modeling, Data modeling and Software modeling
- Conceptual, logical and physical data & process modeling, including languages and notations, model operations, integrity assessment and enforcement (constraints and rules, algorithms and methods), and, design methods
- Data and Software joint modeling, co-design, co-management & evolution
- Ontologies. Models and languages, ontology integration, alignment and reconciliation, ontology exploitation in data engineering (e.g., for querying purposes).
- Model mappings and transformations
- Visualization techniques for data models and data instances
- Data & process model quality: metrics, assessment and usage
Data Engineering Techniques with emphasis on Data Semantics
- Model-driven, forward and reverse engineering for databases, data repositories and processes
- Data and Software Evolution (e.g., studies of schema/software evolution, software and data co-evolution, database evolution at the physical level and its impact)
- Data migration, provenance and curation
- Data integration (handling of diverse data sources with different metamodels, schemata, heterogeneous data values and rules; system interoperability)
There are no restrictions on the types of data managed (indicatively, data can be relational, spatial, temporal, textual, multimodal, web or user-generated content, semantic-web, RDF, JSON, Parquet, …) or the environment that produces or hosts them (indicatively: traditional Information Systems, OLTP, DSS, Data warehouses and Business Intelligence, scientific data management, data lakes, service-oriented architectures, enterprise architectures, web-hosted content, public data sets, …).