Schema Vacuuming in Temporal Databases

Temporal databases facilitate the support of historical information by providing functions for indicating the intervals during which a tuple was applicable (along one or more temporal dimensions). Because data are never deleted, only superceded, temporal databases are inherently append-only resulting, over time, in a large historical sequence of database states. Data vacuuming in temporal databases allows for this sequence to be shortened by strategically, and irrevocably, deleting obsolete data. Schema versioning allows users to maintain a history of database schemata without compromising the semantics of the data or the ability to view data through historical schemata. While the techniques required for data vacuuming in temporal databases have been relatively well covered, the associated area of vacuuming schemata has received less attention. This paper discusses this issue and proposes a mechanism that fits well with existing methods for data vacuuming and schema versioning

Change Management: The Core Task of Ontology Versioning and Evolution

Change management as a key issue in ontology versioning and evolution is still not fully addressed, which to some extent forms a barrier against the smooth process of ontology evolution. The key issue in the support of evolving ontologies is to distinguish and recognize the changes during the process of ontology evolution. Most of the current popular work on ontology versioning do not keep a record of the changes in the ontology, thus preventing the user from tracking those changes back and forward, or to at least understand the rational behind those changes. We are proposing an approach to get the evidences of ontology changes, keep track of them, and manage them in an engineering fashion

A temporal versioned object-oriented data schema model

AbstractThis paper describes in a formal way a data schema model which introduces temporal and versioning schema features in an object-oriented environment. In our model, the schema is time dependent and the history of the changes which occur on its elements are kept into version hierarchies. A fundamental assumption behind our approach is that a new schema specification should not define a new database, so that previous schema definitions are considered as alternative design specifications, and consequently, existing data can be accessed in a consistent way using any of the defined schemas

A Unifying Version Model for Objects and Schema in Object-Oriented Database System

There have been a number of different versioning models proposed. The research in this area can be divided into two categories: object versioning and schema versioning. In this dissertation, both problem domains are considered as a single unit. This dissertation describes a unifying version model (UVM) for maintaining changes to both objects and schema. UVM handles schema versioning operations by using object versioning techniques. The result is that the UVM allows the OODBMS to be much smaller than previous systems. Also, programmers need know only one set of versioning operations; thus, reducing the learning time by half. This dissertation shows that UVM is a simple but semantically sound and powerful version model for both objects and schema

Information Integration - the process of integration, evolution and versioning

At present, many information sources are available wherever you are. Most of the time, the information needed is spread across several of those information sources. Gathering this information is a tedious and time consuming job. Automating this process would assist the user in its task. Integration of the information sources provides a global information source with all information needed present. All of these information sources also change over time. With each change of the information source, the schema of this source can be changed as well. The data contained in the information source, however, cannot be changed every time, due to the huge amount of data that would have to be converted in order to conform to the most recent schema.\ud In this report we describe the current methods to information integration, evolution and versioning. We distinguish between integration of schemas and integration of the actual data. We also show some key issues when integrating XML data sources

Designing Reusable Systems that Can Handle Change - Description-Driven Systems : Revisiting Object-Oriented Principles

In the age of the Cloud and so-called Big Data systems must be increasingly flexible, reconfigurable and adaptable to change in addition to being developed rapidly. As a consequence, designing systems to cater for evolution is becoming critical to their success. To be able to cope with change, systems must have the capability of reuse and the ability to adapt as and when necessary to changes in requirements. Allowing systems to be self-describing is one way to facilitate this. To address the issues of reuse in designing evolvable systems, this paper proposes a so-called description-driven approach to systems design. This approach enables new versions of data structures and processes to be created alongside the old, thereby providing a history of changes to the underlying data models and enabling the capture of provenance data. The efficacy of the description-driven approach is exemplified by the CRISTAL project. CRISTAL is based on description-driven design principles; it uses versions of stored descriptions to define various versions of data which can be stored in diverse forms. This paper discusses the need for capturing holistic system description when modelling large-scale distributed systems.Comment: 8 pages, 1 figure and 1 table. Accepted by the 9th Int Conf on the Evaluation of Novel Approaches to Software Engineering (ENASE'14). Lisbon, Portugal. April 201

A logic programming framework for modeling temporal objects

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Temporal Versioning in Biodiversity Ontology

Abstract — The Indonesian archipelago has an extraordinary biodiversity, and it has dynamic and potentially informative biogeography. Biodiversity Information requires the combined data on living creatures and their habitats, build a model that connects all kinds of information. Heterogeneous data handled, provided and distributed by different research groups, which collects data using a different vocabulary. Ontology adopted as one way to reduce the problem of heterogeneity, thus helping the cooperation between researchers. Thus, in order to provide co-operation group, several types of ontology integration mechanism must be provided. An interface (mediator) to various sources of data needed to integrate information from sources that are used, either by human users or applications programs. Interface (in the form of applications) determine the source of data used and how to get back data from the data sourc