The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

Background. 
The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community.

Description. 
SADI – Semantic Automated Discovery and Integration – is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services “stack”, SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers.

Conclusions.
SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behavior we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in static triple-stores, thus facilitating the intersection of Web services and Semantic Web technologies

Interoperability With Moby 1.0 - It's Better Than Sharing Your Toothbrush!

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry API, and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org

Automatic annotation of bioinformatics workflows with biomedical ontologies

Legacy scientific workflows, and the services within them, often present scarce and unstructured (i.e. textual) descriptions. This makes it difficult to find, share and reuse them, thus dramatically reducing their value to the community. This paper presents an approach to annotating workflows and their subcomponents with ontology terms, in an attempt to describe these artifacts in a structured way. Despite a dearth of even textual descriptions, we automatically annotated 530 myExperiment bioinformatics-related workflows, including more than 2600 workflow-associated services, with relevant ontological terms. Quantitative evaluation of the Information Content of these terms suggests that, in cases where annotation was possible at all, the annotation quality was comparable to manually curated bioinformatics resources.Comment: 6th International Symposium on Leveraging Applications (ISoLA 2014 conference), 15 pages, 4 figure

Magallanes: a web services discovery and automatic workflow composition tool

<p>Abstract</p> <p>Background</p> <p>To aid in bioinformatics data processing and analysis, an increasing number of web-based applications are being deployed. Although this is a positive circumstance in general, the proliferation of tools makes it difficult to find the right tool, or more importantly, the right set of tools that can work together to solve real complex problems.</p> <p>Results</p> <p>Magallanes (Magellan) is a versatile, platform-independent Java library of algorithms aimed at discovering bioinformatics web services and associated data types. A second important feature of Magallanes is its ability to connect available and compatible web services into workflows that can process data sequentially to reach a desired output given a particular input. Magallanes' capabilities can be exploited both as an API or directly accessed through a graphic user interface.</p> <p>The Magallanes' API is freely available for academic use, and together with Magallanes application has been tested in MS-Windows™ XP and Unix-like operating systems. Detailed implementation information, including user manuals and tutorials, is available at <url>http://www.bitlab-es.com/magallanes</url>.</p> <p>Conclusion</p> <p>Different implementations of the same client (web page, desktop applications, web services, etc.) have been deployed and are currently in use in real installations such as the National Institute of Bioinformatics (Spain) and the ACGT-EU project. This shows the potential utility and versatility of the software library, including the integration of novel tools in the domain and with strong evidences in the line of facilitate the automatic discovering and composition of workflows.</p

Functional units: Abstractions for Web service annotations

Computational and data-intensive science increasingly depends on a large Web Service infrastructure, as services that provide a broad array of functionality can be composed into workflows to address complex research questions. In this context, the goal of service registries is to offer accurate search and discovery functions to scientists. Their effectiveness, however, depends not only on the model chosen to annotate the services, but also on the level of abstraction chosen for the annotations. The work presented in this paper stems from the observation that current annotation models force users to think in terms of service interfaces, rather than of high-level functionality, thus reducing their effectiveness. To alleviate this problem, we introduce Functional Units (FU) as the elementary units of information used to describe a service. Using popular examples of services for the Life Sciences, we define FUs as configurations and compositions of underlying service operations, and show how functional-style service annotations can be easily realised using the OWL semantic Web language. Finally, we suggest techniques for automating the service annotations process, by analysing collections of workflows that use those services.</p

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

<p>Abstract</p> <p>Background</p> <p>The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality.</p> <p>Results</p> <p>As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of high-throughput lipidomics.</p> <p>Conclusions</p> <p>Our prototype framework is capable of accurate automated classification of lipids and facile integration of lipid class information with additional data obtained with SADI web services. The potential of programming-free integration of external web services through the SADI framework offers an opportunity for development of powerful novel applications in lipidomics. We conclude that semantic web technologies can provide an accurate and versatile means of classification and annotation of lipids.</p

Using registries to integrate bioinformatics tools and services into workbench environments

The diversity and complexity of bioinformatics resources presents significant challenges to their localisation, deployment and use, creating a need for reliable systems that address these issues. Meanwhile, users demand increasingly usable and integrated ways to access and analyse data, especially within convenient, integrated “workbench” environments. Resource descriptions are the core element of registry and workbench systems, which are used to both help the user find and comprehend available software tools, data resources, and Web Services, and to localise, execute and combine them. The descriptions are, however, hard and expensive to create and maintain, because they are volatile and require an exhaustive knowledge of the described resource, its applicability to biological research, and the data model and syntax used to describe it. We present here the Workbench Integration Enabler, a software component that will ease the integration of bioinformatics resources in a workbench environment, using their description provided by the existing ELIXIR Tools and Data Services Registry