On propagation of deletions and annotations through views
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
DiscoveryLink: a system for integrated access to life sciences data sources
IBM Systems Journal - Deep computing for the life sciences
Database management for life sciences research
ACM SIGMOD Record
DBNotes: a post-it system for relational databases based on provenance
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A survey of data provenance in e-science
ACM SIGMOD Record
Scientific data management in the coming decade
ACM SIGMOD Record
MONDRIAN: Annotating and Querying Databases through Colors and Blocks
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
An annotation management system for relational databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Managing Biological Data using bdbms
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Relational completeness of query languages for annotated databases
DBPL'07 Proceedings of the 11th international conference on Database programming languages
Provenance in Databases: Why, How, and Where
Foundations and Trends in Databases
Modeling and querying provenance by extending CIDOC CRM
Distributed and Parallel Databases
Annotations: dynamic semantics in stream processing
PIKM '10 Proceedings of the 3rd workshop on Ph.D. students in information and knowledge management
Propagation of multi-granularity annotations
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Enhancing scientific information systems with semantic annotations
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Annotations play a key role in understanding and curating databases. Annotations may represent comments, descriptions, lineage information, among several others. Annotation management is a vital mechanism for sharing knowledge and building an interactive and collaborative environment among database users and scientists. What makes it challenging is that annotations can be attached to database entities at various granularities, e.g., at the table, tuple, column, cell levels, or more generally, to any subset of cells that results from a select statement. Therefore, simple comment fields in tuples would not work because of the combinatorial nature of the annotations. In this paper, we present extensions to current database management systems to support annotations. We propose storage schemes to efficiently store annotations at multiple granularities, i.e., at the table, tuple, column, and cell levels. Compared to storing the annotations with the individual cells, the proposed schemes achieve more than an order-of-magnitude reduction in storage and up to 70% saving in the query execution time. We define types of annotations that inherit different behaviors. Through these types, users can specify, for example, whether or not an annotation is continuously applied over newly inserted data and whether or not an annotation is archived when the base data is modified. These annotation types raise several storage and processing challenges that are addressed in the paper. We propose declarative ways to add, archive, query, and propagate annotations. The proposed mechanisms are realized through extensions to the standard SQL. We implemented the proposed functionalities inside PostgreSQL with an easy to use Excel-based front-end graphical interface.