Leonardo Salayandia

Workflow-Driven Ontologies: An Earth Sciences Case Study

A goal of the Geosciences Network (GEON) is to develop cyber-infrastructure that will allow earth scientists to discover access, integrate and disseminate knowledge in distributed environments such as the Web, changing the way in which research is conducted. The earth sciences community has begun the complex task of creating ontologies to support this effort. A challenge is to coalesce the needs of the earth scientists, who wish to capture knowledge in a particular discipline through the ontology, with the need to leverage the knowledge to support technology that will facilitate computation, for example, by helping the composition of services. This paper describes an approach for defining workflow-driven ontologies that capture classes and relationships from domain experts and use that knowledge to support composition of services. To demonstrate the capability afforded by this type of ontology, the paper presents examples of workflow specifications generated from a workflow-driven ontology that has been defined for representing knowledge about gravity data.

PAPI deployment, evaluation, and extensions

PAPI is a cross-platform interface to the hardware performance counters available on most modern microprocessors. These counters exist as a small set of registers that count events, which are occurrences of specific signals related to processor functions. Monitoring these events has a variety of uses in application development, including performance modeling and optimization, debugging, and benchmarking. In addition to routines for accessing the counters, PAPI specifies a common set of performance metrics considered most relevant to analyzing and tuning application performance. These metrics include cycle and instruction counts, cache and memory access statistics, and functional unit and pipeline status, as well as relevant SMP cache coherence events. PAPI is becoming a de facto industry standard and has been incorporated into several third-party research and commercial performance analysis tools. As in any physical system, the act of measuring perturbs the phenomenon being measured. Discrepancies in hardware counts and counter-related profiling data can result from other causes as well. A PET-sponsored project is deploying PAPI and related tools on DoD HPC Center platforms and evaluating and interpreting performance counter data on those platforms.

Using Domain Requirements to Achieve Science-Oriented Provenance

The US Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) is adopting the use of formalized provenance to support observational data products produced by ARM operations and relied upon by researchers. Because of the diversity of needs in the climate community provenance will need to be conveyed in a domain-oriented context. This paper explores a use case where semantic abstract workflows (SAW) are employed as a means to filter, aggregate, and contextually describe the historical events responsible for the ARM data product the scientist is relying upon.

CI-Miner: semantically enhancing scientific processes

The realization of an international cyberinfrastructure of shared resources to overcome time and space limitations is challenging scientists to rethink how to document their processes. Many known scientific process requirements that would normally be considered impossible to implement a few years ago are close to becoming a reality for scientists, such as large scale integration and data reuse, data sharing across distinct scientific domains, comprehensive support for explaining process results, and full search capability for scientific products across domains. This article introduces the CI-Miner approach that can be used to aggregate knowledge about scientific processes and their products through the use of semantic annotations. The article shows how this aggregated knowledge is used to benefit scientists during the development of their research activities. The discussion is grounded on lessons learned through the use of CI-Miner to semantically annotate scientific processes in the areas of geo-sciences, environmental sciences and solar physics: A use case in the field of geo-science illustrates the CI-Miner approach in action.

Towards a workflow management system for service oriented modules

With the emergence of service-oriented architectures (SOAs), workflow management systems are being used to create applications from service compositions. Because service compositions may extend across platforms, domains, and virtual organisations, classical implementations of workflow management systems must be extended to address interoperability and reliability. In particular, there is a need to define interoperable and scalable communication mechanisms to support workflows over loosely-coupled environments and to provide support for runtime verification to increase user confidence in workflow behavior. This paper presents a road map towards creating a scientific workflow management system that leverages SOA and runtime verification technologies.

Semantic annotation of maps through knowledge provenance

Maps are artifacts often derived from multiple sources of data, e.g., sensors, and processed by multiple methods, e.g., gridding and smoothing algorithms. As a result, complex metadata may be required to describe maps semantically. This paper presents an approach to describe maps by annotating associated provenance. Knowledge provenance can represent a semantic annotation mechanism that is more scalable than direct annotation of map. Semantic annotation of maps through knowledge provenance provides several benefits to end users. For example, a user study is presented showing that scientists with different levels of expertise and background are able to evaluate the quality of maps by analyzing their knowledge provenance information.

On the Use of Semantic Abstract Workflows Rooted on Provenance Concepts

Two challenges related to capturing provenance about scientific data are: 1) determining an adequate level of granularity to encode provenance, and 2) encoding provenance in a way that facilitates end-user interpretation and analysis. A solution to address these challenges consists in integrating two technologies: Semantic Abstract Workflows (SAWs), which are used to capture a domain expert’s understanding of a scientific process, and PML, an extensible language used to encode provenance. This paper describes relevant features of these technologies for addressing the granularity and interpretation challenges of provenance encoding and presents a discussion about their integration.

The gravity data ontology: laying the foundation for workflow-driven ontologies

Ontologies can be tailored in ways that can facilitate the description of workflows by specifying how concepts representing services are used to access and create concepts representing data and products. Early work on the development of such ontologies, and reported in this paper, has resulted in the construction of a gravity data ontology. The relationships that are defined in the ontology capture inputs and outputs of methods, e.g., derived data and products, as well as other associations that are related to workflow computation. This paper presents the basis for a computation-driven ontology that evolved into the workflow-driven ontology approach. In addition, the paper describes the process used to construct an ontology for gravity data using the computation-driven approach, and it presents a gravity ontology that documents the processes and methods associated with gravity data and related products.

Program synthesis from Workflow-Driven Ontologies

An approach that results in the development of Workflow-Driven Ontologies (WDO) (called the WDO approach) allows domain scientists to capture process knowledge in the form of concepts as well as relations between concepts. Program synthesis techniques can be employed to generate algorithmic solutions by transforming the process knowledge expressed in the WDO as concepts and relations to variables and functions and computing unknown variables from known ones based on the process knowledge documented by the domain scientist. Furthermore, the algorithmic solutions that are generated by program synthesis potentially can support the composition of services, which result in the creation of executable scientific workflows. The ultimate goal of this work is to provide an end-to-end solution for scientists beginning with modeling the processes for creating work products in terminology from the scientists own domains and ending with component-based applications that can be used to automate processes that can advance their scientific endeavors. These applications can exploit distributed components that are supported by current cyber-infrastructure efforts. This paper discusses extensions to the WDO approach that support program synthesis. To elucidate this scenario, an example related to earth sciences is presented.