Bio-jETI: a framework for semantics-based service composition

Lamprecht, Anna-Lena; Margaria, Tiziana; Steffen, Bernhard

doi:10.1186/1471-2105-10-s10-s8

Cited by 60 publications

(22 citation statements)

References 42 publications

(44 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Other similar efforts include the Moby SW framework [70,71] that offers a semi-automatic web service composition framework for the life sciences domain and the Bio-Jeti project [72] that offers a semantic framework for service composition, particularly emphasizing resolving the issues of type mismatches and model inconsistencies of the composition. Tsiknakis et al [73] report an SW-enabled grid infrastructure that provides integrated access and analysis of multilevel biomedical data in support of multi-centric, post-genomic clinical trials on cancer research.…”

Section: Semantic Web Service and Scientific Collaborationmentioning

confidence: 99%

The use of web ontology languages and other semantic web tools in drug discovery

Chen

2010

Expert Opinion on Drug Discovery

View full text Add to dashboard Cite

i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

show abstract

Section: Semantic Web Service and Scientific Collaborationmentioning

confidence: 99%

The use of web ontology languages and other semantic web tools in drug discovery

Chen

2010

Expert Opinion on Drug Discovery

View full text Add to dashboard Cite

show abstract

“…For instance, the Bio-jETI [15], [16] incarnation of the jABC framework comprises a set of plugins that is adequate for dealing with bioinformatics workflows (esp. Tracer, Genesys, PROPHETS, TaxonomyEditor, GEAR), the LearnLib Studio [17], [18] for management of automata learning processes combines the Tracer and Layouter plug-ins with an additional LearnLib plug-in, and ConnectIT [19] is mainly constituted by a specific plug-in that facilitates the intuitive design and evaluation of game strategies for Connect Four, but makes use of the Tracer for the execution of matches with the developed strategies.…”

Section: The Jabc Frameworkmentioning

confidence: 99%

Simplicity principles for plug-in development: The jABC approach

Naujokat

Lamprecht

Steffen

et al. 2012

2012 Second International Workshop on Developing Tools as Plug-Ins (TOPI)

Self Cite

View full text Add to dashboard Cite

In this paper we present our experiences from a decade of plug-in development in the jABC framework, that is characterized by rigorous application of simplicity principles in two dimensions. First, the scope of the plug-in development is clearly defined: The jABC readily provides a sophisticated graphical user interface, which has been tailored to working with all kinds of directed graphs. Within this scope, plug-in development can deliberately focus on the actual functionality, like providing semantics to graphs, without having to deal with tedious but semantically irrelevant issues like user interfaces. Second, plug-in functionality can be itself conveniently modeled as a workflow within the jABC. We illustrate our approach by means of two mature plug-ins: Genesys, a plug-in that adds arbitrary code generator functionality to the jABC, and PROPHETS, a plug-in that eases user-level definition of workflows by completing model sketches by means of synthesis capabilities, so that they become complete and executable. We summarize our experience so far and derive general design principles for "lightweight plug-in development", that we are going to realize in the next generation of the jABC, which will be implemented itself as a collection of Eclipse plug-ins.

show abstract

“…An exception is Bio-jETI [17,18], which bridges this gap by supporting the incorporation of semantically modeled domain information for control-flow oriented process construction. Its holistic perspective covers both the process modeling and the integration of individual services and platforms:…”

Section: Introductionmentioning

confidence: 99%

Semantics-based composition of EMBOSS services

et al. 2011

Self Cite

View full text Add to dashboard Cite

BackgroundMore than in other domains the heterogeneous services world in bioinformatics demands for a methodology to classify and relate resources in a both human and machine accessible manner. The Semantic Web, which is meant to address exactly this challenge, is currently one of the most ambitious projects in computer science. Collective efforts within the community have already led to a basis of standards for semantic service descriptions and meta-information. In combination with process synthesis and planning methods, such knowledge about types and services can facilitate the automatic composition of workflows for particular research questions.ResultsIn this study we apply the synthesis methodology that is available in the Bio-jETI workflow management framework for the semantics-based composition of EMBOSS services. EMBOSS (European Molecular Biology Open Software Suite) is a collection of 350 tools (March 2010) for various sequence analysis tasks, and thus a rich source of services and types that imply comprehensive domain models for planning and synthesis approaches. We use and compare two different setups of our EMBOSS synthesis domain: 1) a manually defined domain setup where an intuitive, high-level, semantically meaningful nomenclature is applied to describe the input/output behavior of the single EMBOSS tools and their classifications, and 2) a domain setup where this information has been automatically derived from the EMBOSS Ajax Command Definition (ACD) files and the EMBRACE Data and Methods ontology (EDAM). Our experiments demonstrate that these domain models in combination with our synthesis methodology greatly simplify working with the large, heterogeneous, and hence manually intractable EMBOSS collection. However, they also show that with the information that can be derived from the (current) ACD files and EDAM ontology alone, some essential connections between services can not be recognized.ConclusionsOur results show that adequate domain modeling requires to incorporate as much domain knowledge as possible, far beyond the mere technical aspects of the different types and services. Finding or defining semantically appropriate service and type descriptions is a difficult task, but the bioinformatics community appears to be on the right track towards a Life Science Semantic Web, which will eventually allow automatic service composition methods to unfold their full potential.

show abstract

Bio-jETI: a framework for semantics-based service composition

Cited by 60 publications

References 42 publications

The use of web ontology languages and other semantic web tools in drug discovery

The use of web ontology languages and other semantic web tools in drug discovery

Simplicity principles for plug-in development: The jABC approach

Semantics-based composition of EMBOSS services

Contact Info

Product

Resources

About