Víctor Cuevas-Vicenttín

Modeling and Querying Scientific Workflow Provenance in the D-OPM

We present the D-OPM, a model that extends the Open Provenance Model (OPM) with workflow-specific aspects. In particular, our model captures aspects such as the workflow structure, traces, data structure, and workflow evolution. Thus, it enables scientists to obtain detailed information about the origin of data resulting from past experiments, as well as about the process itself and its possible future executions. A reference implementation of the D-OPM validates our model and opens the opportunity for interoperation with multiple workflow systems. Furthermore, to facilitate querying D-OPM data we introduce a querying mechanism based on regular path queries (RPQs) on provenance graphs. Our RPQs evaluator is built on a relational DBMS which makes it robust and extensible.

Scientific Workflows and Provenance: Introduction and Research Opportunities

Scientific workflows are becoming increasingly popular for compute-intensive and data-intensive scientific applications. The vision and promise of scientific workflows includes rapid, easy workflow design, reuse, scalable execution, and other advantages, e.g., to facilitate “reproducible science” through provenance (e.g., data lineage) support. However, as described in the paper, important research challenges remain. While the database community has studied (business) workflow technologies extensively in the past, most current work in scientific workflows seems to be done outside of the database community, e.g., by practitioners and researchers in the computational sciences and eScience. We provide a brief introduction to scientific workflows and provenance, and identify areas and problems that suggest new opportunities for database research.

Coordinating services for accessing and processing data in dynamic environments

This paper presents an approach and an associated system named Hypatia for accessing and processing data by coordinating services in dynamic environments. A dynamic environment consists of applications, servers and devices that can be static and nomad, and that produce or consume data on demand (e.g., online applications, Web-hosted DBMS) or continuously (messaging systems, mobile services). In such an environment, data are hidden behind services that export application programming interfaces (API) through heterogeneous networks and that provide functions for retrieving and processing data. In order to have an aggregated and integrated view of the dynamic environment at every moment (e.g., accessing Googles agenda service and feeding a Twitter service for continuously locating friends as we all stroll in a city), data consumers have to execute sets of service calls, i.e., subscribe to continuous data producers, aggregate results and feed other services and then obtain results and eventually start over again. No off-the-shelf DBMS provides such service oriented querying approach including continuous, one-shot, mobile and static query evaluation. Our work introduces the notion of hybrid query that declaratively expresses data consumers requirements and an associated query evaluator, Hypatia, that executes data oriented query service coordinations; taking advantage of the services available in the network (data providers and devices computing capacity) and yielding the query result.

DataONE: A Data Federation with Provenance Support

DataONE is a federated data network focusing on earth and environmental science data. We present the provenance and search features of DataONE by means of an example involving three earth scientists who interact through a DataONE Member Node. DataONE provenance systems enable reproducible research and facilitate proper attribution of scientific results transitively across generations of derived data products.

Efficiently Coordinating Services for Querying Data in Dynamic Environments

In this paper we present our vision, and discuss the main research problems along with prospective solutions, on the evaluation of queries over data available and processable through services. In particular, we address queries in dynamic environments concerning aspects such as mobility and continuous data. These queries entail the potential of offering users ubiquitous access to relevant information in the form of value-added services. The core of our proposed approach, lies in the development of a services coordination framework complemented with proven traditional query processing techniques adapted to service-based environments. Thus, we derive the blueprint for an efficient solution for query evaluation in service-based contexts and their related application areas.

ANDROMEDA: building e-science data integration tools

This paper presents Andromeda (Astronomical Data Resources Mediation), an XML-based data mediation system that enables transparent access to astronomical data sources. Transparent access is achieved by a global view that expresses the requirements of a community of users (i.e., astronomers) and data integration mechanisms adapted to astronomical data characteristics. Instead of providing an ad hoc mediator, Andromeda can be configured for giving access to different data sources according to user requirements (data types, content, data quality, and provenance). Andromeda can be also adapted when new sources are added or new requirements are specified. Furthermore, in Andromeda the data integration process is done in a distributed manner, taking advantage of the available computing resources and reducing data communication costs.

Provenance-Based Searching and Ranking for Scientific Workflows

We present PBase, a scientific workflow provenance repository that supports declarative graph queries and keyword-based graph searching, complemented with ranking capabilities taking into consideration authority and quality of service criteria. Given the widespread use of scientific workflow systems and the increasing support and relevance of provenance as part of their functionality, the challenge arises to enable scientists to use provenance for the discovery of experiments, programs, and data of interest. PBase aims to satisfy this requirement while also presenting to the user a customized graphical user interface that greatly facilitates the exploration of the repository and the visualization of results.

Web Services Orchestration in the WebContent Semantic Web Framework

We present the design and implementation of a Web services orchestration engine developed to support the WebContent semantic Web framework. This framework is under development in the context of the WebContent project, whose goal is to provide a scalable and robust platform for the development of semantic content management applications for diverse domains. The WebContent framework is based on a set of core services able to perform the main tasks associated with semantic content and data management, as well as on the adoption of a common document model based on XML, which facilitates the exchange and retrieval of information. Our contribution lies in providing the necessary infrastructure to effectively and efficiently coordinate the diverse services and data sources, thus facilitating the rapid development of flexible and reliable applications.

Provenance Storage, Querying, and Visualization in PBase

We present PBase, a repository for scientific workflows and their corresponding provenance information that facilitates the sharing of experiments among the scientific community. PBase is interoperable since it uses ProvONE, a standard provenance model for scientific workflows. Workflows and traces are stored in RDF, and with the support of SPARQL and the tree cover encoding, the repository provides a scalable infrastructure for querying the provenance data. Furthermore, through its user interface, it is possible to: visualize workflows and execution traces; visualize reachability relations within these traces; issue SPARQL queries; and visualize query results.

A Planning-Based Service Composition Approach for Data-Centric Workflows

This paper presents a planning-based approach for the enumeration of alternative data-centric workflows specified in ASASEL (Abstract State mAchineS Execution Language), which define the coordination of data and computation services for satisfying data requirements. The optimization of data-centric workflows is associated to the exploration of the parallelization of the workflow activities. We address the exploration of parallelism formalizing the enumeration problem in the DLV-K language. Together, our ASASEL language and enactment engine along with our enumeration approach provide the foundation for a highly flexible mechanism for managing data-centric workflows.