Knowledge of structure is critical to map legacy workflows to environments suitable to run on the cloud. We present a method which characterizes a workflow structure with the execution trace produced by instrumented logging functionality. The method generates the structure of workflows to support their reuse by permitting their transformation into modern execution environments. The method presented in the paper is implemented for Python workflows and demonstrated in the context of several legacy scientific workflows.

Scientific discovery relies on an experimental framework that corroborates hypotheses with experiments that are complex reproducible processes generating and transforming large datasets. The methods, implicit in the process, capture the semantics of the data, thus they are responsible for the generation of scientific information and discovery of scientific knowledge. Scientific workflows provide the semantics needed to wrap scientific data from their capture, analysis, publication, and archival. By annotating data with the processes that produce them, the scientist no longer manages data but information and allows their meaningful interpretation and integration. Any change to a scientific workflow may impact significantly the quality of the data produced, their semantics, their future analysis, use, integration, and distribution, as well as the performance of the execution. Yet, scientific workflows are typically transformed over time, updated with new versions of the tools that compose them, extended to new functionality, and composed. In this paper we discuss the various impacts of workflow transformation and illustrate them with a case study on the Structural Prediction for pRotein fOlding UTility System (SPROUTS) Workflow.

We investigate the use of time-frequency (TF) methods to query biological sequences in search of regions of similarity or critical relationships among the sequences. Existing querying approaches are insensitive to repeats, especially in low-complexity regions, and do not provide much support for efficiently querying sub-sequences with inserts and deletes (or gaps). Our approach uses highly-localized basis functions and multiple transformations in the TF plane to map characters in a sequence as well as different properties of a sub-sequence, such as its position in the sequence or number of gaps between sub-sequences. We analyze gapped query-based alignment methods using transformations in the TF plane while demonstrating the method's possible operation in real-time without pre-processing. The algorithm's performance is compared to the widely-accepted BLAST alignment approach, and a significance improvement is observed for queries with repetitive segments.

The use of workflow models to integrate intelligently complex experimental and analytical processes is becoming more and more critical to support scientific discovery. Storing and providing querying capabilities to retrieve, import, re-use, adapt, and reason about workflows are becoming necessary components to workflow architectures supporting collaborative and translational research. We report on the evaluation of ProtocolDB a database that supports workflow design and storage conducted at the Translational Genomics Research Institute (TGen).

We present a deductive approach that supports resource discovery. The BiOnMap Web service is designed to support the selection of resources suitable to implement specific tasks. The BiOnMap service is comprised of a metadata catalog and a reasoning engine. The metadata catalog uses domain ontologies to annotate resources semantically and express domain rules that capture path equivalences at the level of the ontology graph. The BiOnMap reasoning engine is able to infer new properties of services to support service discovery, composition, and mapping. We illustrate our approach with an application case from the domain of bioinformatics.

Resource discovery systems often rely on a classification of known resources in order to identify resources suitable for a particular task. In this paper we address the problem of semantic classification vs. syntactic classification. In particular we analyze the BioMoby repository and present the approach used in ProtocolDB to store biological resources with respect to a domain ontology.

We address the problem of service composition to implement complex scientific workflows. The BioOn-Map approach exploits domain ontologies to develop sound and scalable methods to compose and reconciliate automatically bioinformatics services invoked within a scientific workflow.

We propose an efficient storage strategy to record bioinformatics workflows. Our approach presents scientists with a flexible design model that distinguishes the scientific aim as a design protocol expressed against an ontology from the implementations (s), scientific workflows composed of bioinformatics services, and their execution. The storage strategy presented in this paper allows efficient access and constitutes the framework for reasoning on scientific protocols and experimental data.

We present a semantic map of resources for structural bioinformatics applied to proteins, i.e., various methods to predict and analyze protein structures in silico. Our map depicts resources on two levels: a logical level that provides a high-level description of the scientific concepts using a domain ontology; a physical level, that describes the actual resources implementing these connections. Scientists can use our system to express a query that captures their scientific aim, and are guided to identify the resources best meeting their needs. It is intended to provide scientists a tool to register and share knowledge about the available services in this field. Our approach addresses the problem of semantic interoperability of scientific resources publicly available on the Web

Geographic data have been collected for centuries and are available in a wide variety of formats and supports. VirGIS provides an integrated view of the data, and a geographical query language to access and manipulate integrated geographical data. Typical mediation approaches are data-driven and do not address the problem of integration of query capabilities. Geographic languages provided by GIS usually express spatial selections, metric or topological queries, allocations, etc., in addition to standard data manipulation. the VirGIS mediation system aims to integrate geographical query capabilities with GQuery, a XML geographical query language, and recent specifications published by the Open GIS Consortium (OGC) and adopted by major GIS vendors.

The proliferation of spatial data on the Internet is beginning to allow a much wider access to data currently available in various Geographic Information Systems (GIS). In order to provide effective spatial database integration, we need to provide flexible and powerful GIS data integration solutions. Indeed, GIS are highly heterogeneous: not only they differ by their data representations, but they also offer radically different query languages. A GIS mediation approach should provide an integrated view of the data supplied by all sources, and a geographical query language to access and manipulate integrated data.

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web as well as data generated by software. We present an approach to wrapping web data sources, databases, flat files, or data generated by tools through a database view mechanism. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, second builds the expected output with respect to the virtual structure. Our wrappers are composed of a retrieval component based on an intermediate object view mechanism called search views mapping the source capabilities to attributes, and an eXtensible Markup Language (XML) engine, respectively, to perform these two tasks. The originality of the approach consists of: 1) a generic view mechanism to access seamlessly data sources with limited capabilities and 2) the ability to wrap data sources as well as the useful specific tools they may provide. Our approach has been developed and demonstrated as part of the multidatabase system supporting queries via uniform object protocol model (OPM) interfaces.

Today, scientific data is inevitably digitized, stored in a variety of heterogeneous formats, and is accessible over the Internet. Scientists need to access an integrated view of multiple remote or local heterogeneous data sources. They then integrate the results of complex queries and apply further analysis and visualization to support the task of scientific discovery. Building a digital library for scientific discovery requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web, as well as data that is locally materialized in warehouses or is generated by software. We consider several tasks to provide optimized and seamless integration of biomolecular data. Challenges to be addressed include capturing and representing source capabilities; developing a methodology to acquire and represent metadata about source contents and access costs; and decision support to select sources and capabilities using cost based and semantic knowledge, and generating low cost query evaluation plans.

If XML is to play the critical role of the lingua franca for Internet data interchange that many predict, it is necessary to start designing and adopting benchmarks allowing the comparative performance analysis of the tools being developed and proposed. The effectiveness of existing XML query languages has been studied by many, with a focus on the comparison of linguistic features, implicitly reflecting the fact that most XML tools exist only on paper. In this paper, with a focus on efficiency and concreteness, we propose a pragmatic first step toward the systematic benchmarking of XML query processing platforms with an initial focus on the data (versus document) point of view. We propose XOO7, an XML version of the OO7 benchmark. We discuss the applicability of XOO7, its strengths, limitations and the extensions we are considering. We illustrate its use by presenting and discussing the performance comparison against XOO7 of three different query processing platforms for XML.

Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or from documents retrieved from the World Wide Web. We present an approach to querying flat files as well as Web data sources through an object database view based on a database system and a wrapper. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, secondly builds the expected output with respect to the virtual structure. Scientific data servers, and in particular the ones publicly available on the Web, usually provide information retrieval techniques to access data. Our wrappers are composed of a retrieval component, based on an intermediate object view mechanism called 'search views' mapping the source capabilities to attributes, and a XML engine to perform these two tasks. If the retrieval component is specific to each data source, this approach shows that the extraction component (the XML engine) can be common. We describe our system and focus on the retrieval component of the Object-Web Wrapper (OWW) for Web sources. The originality of our approach consists of (1) a common wrapper architecture for flat files and Web data sources sharing a XML engine for data extraction, (2) a generic view mechanism to access data sources with limited capabilities, and (3) the representation of hyperlinks as abstract attributes in the object view as well as their use in the search view. Our approach has been developed and demonstrated as part of a multidatabase system supporting queries via uniform Object Protocol Model (OPM) interfaces.

Standard database approaches to querying information on the Web focus on the source(s) and provide a query language based on a given predefined organization (schema) of the data: this is the source-driven approach. However, can the Web be seen as a standard database? There is no super-user in charge of monitoring the source(s) (the data is constantly updated), there is no homogeneous structure (no common explicit structure thus), the Web itself never stops growing, etc. For these reasons, we believe that the source-driven standard approach is not suitable to the Web.