Schema Evolution publication categorizer

Summary: Life science ontologies substantially change over time to meet the requirements of their users and to include the newest domain knowledge. Thus, an important task is to know what has been modified between two versions of an ontology (diff ). This diff should contain all performed changes as compact and understandable as possible. We present CODEX (Complex Ontology Diff Explorer), a tool that allows determining semantic changes between two versions of an ontology which users can interactively analyze in multiple ways.

HECATAEUS is an open-source software tool for enabling impact prediction, what-if analysis, and regulation of relational database schema evolution. We follow a graph theoretic approach and represent database schemas and database constructs, like queries and views, as graphs. Our tool enables the user to create hypothetical evolution events and examine their impact over the overall graph before these are actually enforced on it.

We present XBenchMatch, a benchmark which uses as input the result of a schema matching algorithm (set of mappings and/or an integrated schema) and generates statistics about the quality of this input and the performance of the matching tool.

Schemr is a schema search engine, and provides users the ability to search for and visualize schemas stored in a metadata repository. Users may search by keywords and by example -- using schema fragments as query terms. Schemr uses a novel search algorithm, based on a combination of text search and schema matching techniques, as well as a structurally-aware scoring metric. Schemr presents search results in a GUI that allows users to explore which elements match and how well they do. The GUI supports interactions, including panning, zooming, layout and drilling-in.

This demonstration presents Galaxy, a schema manager that facilitates easy and correct data sharing among autonomous but related, evolving data sources. Galaxy reduces heterogeneity by helping database developers identify, reuse, customize, and advertise related schema components. The central idea is that as schemata are customized, Galaxy maintains a derivation graph, and exploits it for matching, data exchange, discovery, and multidatabase query over the “galaxy” of related data sources.

We introduce the +Spicy mapping system. The system is based on a number of novel algorithms that contribute to increase the quality and expressiveness of mappings. +Spicy integrates the computation of core solutions in the mapping generation process in a highly efficient way, based on a natural rewriting of the given mappings. This allows for an efficient implementation of core computations using common runtime languages like SQL or XQuery and guarantees very good performances, orders of magnitude better than those of previous algorithms.

Databases are continuously evolving environments, where design constructs are added, removed or updated rather often. Small changes in the database configurations might impact a large number of applications and data stores around the system: queries and data entry forms can be invalidated, application programs might crash. HECATAEUS is a tool, which represents the database schema along with its dependent workload, mainly queries and views, as a uniform directed graph.

Schema evolution poses serious challenges in historical data management. Traditionally the archival data has been (i) either migrated under the current schema version, to ease querying, but compromising archival quality, or (ii) maintained under the original schema version in which they firstly appeared, leading to a perfect archival quality, but to a taxing query interface.

DEMO PAPER:

We demonstrate a prototype that translates schemas from a source metamodel (e.g., OO, relational, XML) to a target metamodel. The prototype is integrated with Microsoft Visual Studio 2005 to generate relational schemas from an object-oriented design. It has four novel features. First, it produces instance mappings to round-trip the data between the source schema and the generated target schema. It compiles the instance mappings into SQL views to reassemble the objects stored in relational tables.

The structure of XML documents, expressed as XML schemas [6], can evolve as well as their content. Systems must be frequently adapted to real-world changes or updated to fix design errors and thus data structures must change accordingly in order to address the new requirements. A consequence of schema evolution is that documents instance of the original schema might not be valid anymore. Currently, users have to explicitly revalidate the documents and identify the parts to be updated. Moreover, once the parts that are not valid anymore have been identified, they have to be explicitly updated.