Schema Evolution publication categorizer

In den Lebenswissenschaften haben sich Ontologien in den letzten Jahren auf breiter Front durchgesetzt und sind in vielen Anwendungs- und Analyseszenarien kaum mehr wegzudenken. So etablierten sich nach und nach immer mehr domänenspezifische Ontologien, z.B. Anatomie-Ontologien oder Ontologien zur Beschreibung der Funktionen von Genen oder Proteinen. Da das Wissen in den Lebenswissenschaften sich rapide ändert und weiterentwickelt, müssen die entsprechenden Ontologien ständig angepasst und verändert werden, um einen möglichst aktuellen Wissensstand zu repräsentieren.

Learning to Map between Structured Representations of Data

Integration, transformation, and translation of data is increasingly important for modern
information systems and e-commerce applications. Views, and more generally, transformation
specifications, or mappings, provide the foundation for many data transformation
applications.
Mappings are usually specified manually by data administrators that are familiar with
the semantics of the data and have a good knowledge of the transformation language. The
task of generating and managing mappings is laborious, time consuming and error-prone

“Nothing endures but change. ” –By Heractilus Change is inevitable even for persistent information. Effectively managing change of persistent information, which includes the specification, execution and the maintenance of any derived information, is critical and must be addressed by all database systems. Today, for every data model there exists a well-defined set of change primitives that can alter both the structure (the schema) and the data. Several proposals also exist for incrementally propagating a primitive change to any derived information (or view).

Experience shows that even after programs have been designed, built and tested, change
is more the norm than the exception. Consider a shared object-oriented persistent system
built to serve the business needs of a company. Changes such as additions of classes or
class members, renamings, retypings, etc. may be needed to introduce new applications,
enhance existing ones, or integrate separately built systems. Additional changes such as
factoring out duplicate code, rearranging the class hierarchy and delegating responsibilities

Continuously arising new trends in information technology and developments at the (e–business)
market let companies crave for automated business process support. Process management systems offer
the promising possibility to (electronically) define, control, and monitor business processes. However, if
this technology shall be applicable in practice it must be possible to change running business processes
even at runtime. Basically, such process changes can take place at two levels – the process type level

New application areas for databases like data warehousing and OLAP (Online Analytical Processing)deploy the multidimensional data model in order to describe the application domain. Consequently, OLAP systems are represented by a multidimensional database schema to adequately reflect the application semantics.
FIESTA presents a methodology for the evolution of such multidimensional schemas. Core of
the thesis is a schema evolution algebra which comprehends a formal multidimensional data
model together with corresponding schema evolution operations. Since OLAP systems are

Many challenging problems facing information systems engineering involve
the manipulation of complex metadata artifacts, or models, such as database
schemas, interface specifications, or object diagrams, and mappings between
models. The applications that solve metadata manipulation problems are
complex and hard to build. The goal of generic model management is to
reduce the amount of programming needed to develop such applications by
providing a database infrastructure in which a set of high-level algebraic
operators, such as Match, Merge, and Compose, are applied to models and

Schema matching aims at identifying semantic correspondences between elements of two schemas, e.g., database schemas, ontologies, and XML message formats. It is needed in many database applications, such as integration of web data sources, data warehouse loading and XML message mapping. In today's systems, schema matching is manual; a time-consuming, tedious, and error-prone process, which becomes increasingly impractical with a higher number of schemas and data sources to be dealt with.

As information on the World Wide Web continues to proliferate at an astounding rate, the Extensible Markup Language (XML) has been emerging as a standard format for data representation on the web. In many application domains, specific document type definitions (DTDs) are designed to enforce a semantically agreed-upon structure of the XML documents. In XML context, these structural definitions serve as schemata.

XML documents are a typical kind of semistructured data. The usage of XML has increased significantly since 1998, when the XML recommendation was released. The structure of XML documents can be described using a Document Type Definition (DTD). Documents are called valid documents if their structure corresponds to a DTD. If the structure of a DTD changes, it is desirable to apply these changes to documents that are valid with respect to this DTD. These transformations are called evolution. This paper shows how different changes to the DTD effect XML documents.

XML is often used as a data exchange format or it is used for data storage in database systems and distributed information systems. While the usage of XML-Schema for validating the documents, several demands exist what will happen with documents next to the evolution of schemas.
This paper introduces an update-language especially for XML-Schema to carry out the steps of evolution. It also explains how to generate new queries for adapting the documents or XQuery-queries to the evolutionsteps.