Ontology evolution

Ontology management and evolution for business intelligence

Authors: 
Mikroyannidis, A; Theodoulidis, B
Year: 
2010
Venue: 
Journal of Information Management

The amount of heterogeneous data that is available to organizations nowadays has made information management a seriously complicated task, yet crucial since this data can be a valuable asset for business intelligence. Ontologies can act as a semantically rich knowledge base in systems that specialize in information management. The present work investigates the potential of ontologies in supporting the information lifecycle within a corporate environment for business intelligence.

Impact of Ontology Evolution on Functional Analyses

Authors: 
Groß, A; Hartung, M; Prüfer, K; Kelso, J; Rahm, E
Year: 
2012
Venue: 
Bioinformatics

Motivation: Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here we investigate to what degree modifications of the Gene Ontology impact these statistical analyses for both experimental and simulated data.

GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution

Authors: 
Kirsten, T.; Gross, A.; Hartung, M.; Rahm, E.
Year: 
2011
Venue: 
Journal of Biomedical Semantics 2011, 2:6

Background
Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data.

Results

COnto-Diff : Generation of Complex Evolution Mappings for Life Science Ontologies

Authors: 
Hartung, M.; Gross, A.; Rahm, E.
Year: 
2012
Venue: 
Journal of Biomedical Informatics

Life science ontologies evolve frequently to meet new requirements or to better reflect the current domain knowledge. The development and adaptation of large and complex ontologies is typically performed collaboratively by several curators. To effectively manage the evolution of ontologies it is essential to identify the difference (Diff) between ontology versions. Such a Diff supports the synchronization of changes in collaborative curation, the adaptation of dependent data such as annotations, and ontology version management.

CODEX: Exploration of semantic changes between ontology versions

Authors: 
Hartung, M.; Groß, A.; Rahm, E.
Year: 
2012
Venue: 
Bioinformatics 28 (6): 895-896

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.

Recent advances in schema and ontology evolution

Authors: 
Hartung, M.; Terwilliger, J.; Rahm, E.
Year: 
2011
Venue: 
Schema Matching and Mapping

Schema evolution is the increasingly important ability to adapt deployed schemas to changing requirements. Effective support for schema evolution is challenging since schema changes may have to be propagated, correctly and efficiently, to instance data and dependent schemas, mappings, or applications.

Evolution von Ontologien in den Lebenswissenschaften

Authors: 
Hartung, M.
Year: 
2011

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.

Rule-based Generation of Diff Evolution Mappings between Ontology Versions

Authors: 
Hartung, M; Gross, A; Rahm, E
Year: 
2010
Venue: 
Arxiv preprint arXiv:1010.0122, Univ. of Leipzig, 2010

Ontologies such as taxonomies, product catalogs or
web directories are heavily used and hence evolve frequently
to meet new requirements or to better reflect the current instance
data of a domain. To effectively manage the evolution
of ontologies it is essential to identify the difference (Diff) between
two ontology versions. We propose a novel approach to
determine an expressive and invertible diff evolution mapping
between given versions of an ontology. Our approach utilizes
the result of a match operation to determine an evolution

Discovering Evolving Regions in Life Science Ontologies

Authors: 
Hartung, M; Gross, A; Kirsten, T; Rahm, E
Year: 
2010
Venue: 
Data Integration in the Life Sciences (DILS)

Ontologies are heavily used in life sciences and evolve continuously to incorporate new or changed insights. Often ontology changes affect only specific parts (regions) of ontologies making it valuable for ontology users and applications to know the heavily changed regions on the one hand and stable regions on the other hand. However, the size and complexity of life science ontologies renders manual approaches to localize changing or stable regions impossible. We therefore propose an approach to automatically discover evolving or stable ontology regions.

Evolution of the Sequence Ontology terms and relationships

Authors: 
Eilbeck, K; Mungall, CJ
Year: 
2009
Venue: 
J Biomed Inform.

The Sequence Ontology is an established ontology, with a large user community, for the purpose of genomic annotation. We are reforming the ontology to provide better terms and relationships to describe the features of biological sequence, for both genomic and derived sequence. The SO is working within the guidelines of the OBO Foundry to provide interoperability between SO and the other related OBO ontologies. Here, we report changes and improvements made to SO including new relationships to better define the mereological, spatial and temporal aspects of biological sequence.

A Versioning Management Model for Ontology-Based Data Warehouses

Authors: 
Xuan, D; Bellatreche, L; Pierra, G
Year: 
2006
Venue: 
Proc. DAWAK 2006, LNCS 4081

More and more integration systems use ontologies to solve the problem of semantic heterogeneities between autonomous databases. To automate the integration process, a number of these systems suppose the existence of a shared domain ontology a priori referenced by the local ontologies embedded in the various sources. When the shared ontology evolves over the time, the evolution may concern (i) the ontology level, (2) the local schema level, and/or (3) the contents of sources.

Ontology and Schema Evolution in Data Integration: Review and Assessment

Authors: 
Kondylakis, H; Flouris, G; Plexousakis, D
Year: 
2009
Venue: 
OTM 2009, LNCS 5871

The development of new techniques and the emergence of new high- throughput tools have led to a new information revolution. The amount and the diversity of the information that need to be stored and processed have led to the adoption of data integration systems in order to deal with information extraction from disparate sources. The mediation between traditional databases and ontologies has been recognized as a cornerstone issue in bringing in legacy data with formal semantic meaning.

Evaluating the validity of data instances against ontology evolution over the Semantic Web

Authors: 
Qin, L; Atluri, V
Year: 
2009
Venue: 
Information and Software Technology

It is natural for ontologies to evolve over time. These changes could be at structural and semantic levels. Due to changes to an ontology, its data instances may become invalid, and as a result, may become non-interpretable. In this paper, we address precisely this problem, validity of data instances due to ontological evolution. Towards this end, we make the following three novel contributions to the area of Semantic Web. First, we propose formal notions of structural validity and semantic validity of data instances, and then present approaches to ensure them.

Ontology Evolution: State of the Art and Future Directions

Authors: 
Leenheer, P De; Mens, T
Year: 
2008
Venue: 
Ontology Management

The research area of ontology engineering seems to have reached a certain level of maturity, considering the vast amount of contemporary methods and tools for formalising and applying knowledge representation models. However, there is still little understanding of, and support for, the evolutionary aspects of ontologies. This is particularly crucial in distributed and collaborative settings such as the Semantic Web, where ontologies naturally co-evolve with their communities of use.

DOGMA-MESS: A Tool for Fact-Oriented Collaborative Ontology Evolution

Authors: 
Leenheer, P De; Debruyne, C
Year: 
2008
Venue: 
OTM workshops, LNCS 5333

Ontologies being shared formal specifications of a domain, are an important lever for developing meaningful internet systems. However, the problem is not in what ontologies are, but how they become operationally relevant and sustainable over longer periods of time. Fact-oriented and layered approaches such as DOGMA have been successful in facilitating domain experts in representing and understanding semantically stable ontologies, while emphasising reusability and scalability.

Evolva: A Comprehensive Approach to Ontology Evolution

Authors: 
Zablith, F
Year: 
2009
Venue: 
Proc. 6th European Semantic Web Conf.

Ontology evolution is increasingly gaining momentum in the area of Semantic Web research. Current approaches target the evolution in terms of either content, or change management, without covering both aspects in the same framework. Moreover, they are slowed down as they heavily rely on user input. We tackle the aforementioned issues by proposing Evolva, a comprehensive ontology evolution framework, which handles a complete ontology evolution cycle, and makes use of background knowledge for decreasing user input.

On Detecting High-Level Changes in RDF/S KBs

Authors: 
Papavassiliou, V; Flouris, G; Fundulaki, I; D Kotzinos, V ..
Year: 
2009
Venue: 
Proc. ISWC, LNCS 5823

An increasing number of scientific communities rely on Semantic Web ontologies to share and interpret data within and across research domains. These common knowledge representation resources are usually developed and
maintained manually and essentially co-evolve along with experimental evidence produced by scientists worldwide. Detecting automatically the differences between (two) versions of the same ontology in order to store or visualize their

Understanding ontology evolution: A change detection approach

Authors: 
Plessers, P; Troyer, O De; Casteleyn, S
Year: 
2007
Venue: 
Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 5 (1)

In this article, we propose a change detection approach in the context of an ontology evolution framework for OWL DL ontologies. The framework allows ontology engineers to request and apply changes to the ontology they manage. Furthermore, the framework assures that the ontology and its depending artifacts remain consistent after changes have been applied. Innovative is that the framework includes a change detection mechanism that allows generating automatically a detailed overview of changes that have occurred based on a set of change definitions.

Tracking changes during ontology evolution

Authors: 
Noy, NF; Kunnatur, S; Klein, M; Musen, MA
Year: 
2004
Venue: 
Proc. ICSW, LNCS

As ontology development becomes a collaborative process, developers face the problem of maintaining versions of ontologies akin to maintaining versions of software code or versions of documents in large projects. Traditional versioning systems enable users to compare versions, examine changes, and accept or reject changes. However, while versioning systems usually treat software code and text documents as text files, a versioning system for ontologies must compare and present structural changes rather than changes in text representation of ontologies.

Efficient Management of Biomedical Ontology Versions

Authors: 
Kirsten, T; Hartung, M; Gross, A; Rahm, E
Year: 
2009
Venue: 
4th Intl. Workshop on Ontology Content (Part of the OTM Conferences & Workshops)

Ontologies have become very popular in life sciences and other domains. They mostly undergo continuous changes and new ontology versions are frequently released. However, current analysis studies do not consider the ontology changes reflected in different versions but typically limit themselves to a specific ontology version which may quickly become obsolete. To allow applications easy access to different ontology versions we propose a central and uniform management of the versions of different biomedical ontologies.

An evolution-based approach for assessing ontology mappings - A case study in the life sciences

Authors: 
Thor, A; Hartung, M; Gross, A; Kirsten, T; Rahm, E
Year: 
2009
Venue: 
Proc. of 13. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW)

Ontology matching has been widely studied. However, the resulting ontology mappings can be rather unstable when the participating ontologies or utilized secondary sources (e.g., instance sources, thesauri) evolve. We propose an evolution-based approach for assessing ontology mappings by annotating their correspondences by information about similarity values for past ontology versions. These annotations allow us to assess the stability of correspondences over time and they can thus be used to determine better and more robust ontology mappings.

Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Authors: 
Gross, A; Hartung, M; Kirsten, T; Rahm, E
Year: 
2009
Venue: 
6th Intl. Workshop on Data Integration in the Life Sciences (DILS)

Ontology-based annotations associate objects, such as genes and proteins, with well-defined ontology concepts to semantically and uniformly describe object properties. Such annotation mappings are utilized in different applications and analysis studies whose results strongly depend on the quality of the used annotations. To study the quality of annotations we propose a generic evaluation approach considering the annotation generation methods (provenance) as well as the evolution of ontologies, object sources, and annotations.

OnEX: Exploring changes in life science ontologies

Authors: 
Hartung, M; Kirsten, T; Gross, A; Rahm, E
Year: 
2009
Venue: 
BMC Bioinformatics

Background
Numerous ontologies have recently been developed in life sciences to support a consistent annotation of biological objects, such as genes or proteins. These ontologies underlie continuous changes which can impact existing annotations. Therefore, it is valuable for users of ontologies to study the stability of ontologies and to see how many and what kind of ontology changes occurred.

Results

Information Systems Integration and Evolution: Ontologies at Rescue

Authors: 
Curino, Carlo A.; Tanca, Letizia; Zaniolo, Carlo
Year: 
2008
Venue: 
STSM

The life of a modern Information System is often characterized by (i) a push toward integration with other systems, and (ii) the evolution of its data management core in response to continuously changing application requirements. Most of the current proposals dealing with these issues from a database perspective rely on the formal notions of mapping and query rewriting.

Management von Ontologien in den Lebenswissenschaften

Authors: 
Hartung, M.
Year: 
2008
Venue: 
20. Workshop über die Grundlagen von Datenbanken (GvDB)

Die Bedeutung bzw. der praktische Nutzen von Ontologien zeigt sich insbesondere in den Lebenswissenschaften. Durch die gestiegene Akzeptanz und Anwendung von Ontologien stellt deren Management mehr und mehr ein wichtiges Problem dar. Aus diesen Grund werden die ständige Weiterentwicklung (Evolution) von Ontologien und die starke Heterogenität bezüglich ihrer Formate in diesem Beitrag näher betrachtet. Im speziellen versucht ein erster Ansatz verschiedene Ontologien über eine Middleware in Gridumgebungen zu integrieren, um Gridnutzern bzw.

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