Adianto Wibisono

Addressing Big Data challenges for Scientific Data Infrastructure

This paper discusses the challenges that are imposed by Big Data Science on the modern and future Scientific Data Infrastructure (SDI). The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science. The paper proposes the SDI generic architecture model that provides a basis for building interoperable data or project centric SDI using modern technologies and best practices. The paper explains how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services provisioning model.

WS-VLAM: towards a scalable workflow system on the grid

Large scale scientific applications require extensive support from middleware and frameworks that provide the capabilities for distributed execution in the Grid environment. In particular, one of the examples of such frameworks is a Grid-enabled workflow management system. In this paper we present WS-VLAM workflow management system, describe its current design and the developments targeting to support efficient and scalable execution of large workflow applications on the Grid.

VLAM-G: Interactive data driven workflow engine for Grid-enabled resources

Grid brings the power of many computers to scientists. However, the development of Grid-enabled applications requires knowledge about Grid infrastructure and low-level API to Grid services. In turn, workflow management systems provide a high-level environment for rapid prototyping of experimental computing systems. Coupling Grid and workflow paradigms is important for the scientific community: it makes the power of the Grid easily available to the end user. The paradigm of data driven workflow execution is one of the ways to enable distributed workflow on the Grid. The work presented in this paper is carried out in the context of the Virtual Laboratory for e-Science project. We present the VLAM-G workflow management system and its core component: the Run-Time System (RTS). The RTS is a dataflow driven workflow engine which utilizes Grid resources, hiding the complexity of the Grid from a scientist. Special attention is paid to the concept of dataflow and direct data streaming between distributed workflow components. We present the architecture and components of the RTS, describe the features of VLAM-G workflow execution, and evaluate the system by performance measurements and a real life use case.

Scientific workflow management: between generality and applicability

In a problem solving environment (PSE), a scientific workflow management system (SWMS) provides a meta environment for managing activities and data in scientific experiments, for prototyping experimental computing systems and for orchestrating the runtime system behaviour. The realisation of a SWMS is often driven by domain specific applications and thus is at application level. Investigating the common characteristics in domain specific SWMSs and encapsulating them in a generic framework improve the reusability of the SWMS components and reduce the costs for introducing an e-science framework in a new science domain. In this position paper, we present our research in an ongoing project: virtual laboratory for e-science (VL-e). In the VL-e project, we are building a generic e-science framework which would support scientists from different domains to share their knowledge and to perform specific experiments. We summarise the lessons we have learned from a previous VL-e implementation, and discuss the plan for improving the quality of the SWMS support in the VL-e framework.

WS-VLAM: A GT4 Based Workflow Management System

Generic Grid middleware, e.g., Globus Toolkit 4 (GT4), provides basic services for scientific workflow management systems to discover, store and integrate workflow components. Using the state of the art Grid services can advance the functionality of workflow engine in orchestrating distributed Grid resources. In this paper, we present our work on migrating VLAM-G, a Grid workflow engine based on GT2 to GT4. We discuss how we use the rich set of services provided by GT4 in the new design to realize the user interactivity, interoperability and monitoring. The experiment results show that use cases from previous systems can be migrated seamlessly into the new architecture.

Hubble: Linked Data Hub for Clinical Decision Support

The AERS datasets is one of the few remaining, large publicly available medical data sets that until now have not been published as Linked Data. It is uniquely positioned amidst other medical datasets. This paper describes the Hubble prototype system for clinical decision support that demonstrates the speed, ease and flexibility of producing and using a Linked Data version of the AERS dataset for clinical practice and research.

Service-oriented visualization applied to medical data analysis

With the era of Grid computing, data driven experiments and simulations have become very advanced and complicated. To allow specialists from various domains to deal with large datasets, aside from developing efficient extraction techniques, it is necessary to have available computational facilities to visualize and interact with the results of an extraction process. Having this in mind, we developed an Interactive Visualization Framework, which supports a service-oriented architecture. This framework allows, on one hand visualization experts to construct visualizations to view and interact with large datasets, and on the other hand end-users (e.g., medical specialists) to explore these visualizations irrespective of their geographical location and available computing resources. The image-based analysis of vascular disorders served as a case study for this project. The paper presents main research findings and reports on the current implementation status.

Generating Scientific Documentation for Computational Experiments Using Provenance

Electronic notebooks are a common mechanism for scientists to document and investigate their work. With the advent of tools such as IPython Notebooks and Knitr, these notebooks allow code and data to be mixed together and published online. However, these approaches assume that all work is done in the same notebook environment. In this work, we look at generating notebook documentation from multi-environment workflows by using provenance represented in the W3C PROV model. Specifically, using PROV generated from the Ducktape workflow system, we are able to generate IPython notebooks that include results tables, provenance visualizations as well as references to the software and datasets used. The notebooks are interactive and editable, so that the user can explore and analyze the results of the experiment without re-running the workflow. We identify specific extensions to PROV necessary for facilitating documentation generation. To evaluate, we recreate the documentation website for a paper which won the Open Science Award at the ECML/PKDD 2013 machine learning conference. We show that the documentation produced automatically by our system provides more detail and greater experimental insight than the original hand-crafted documentation. Our approach bridges the gap between user friendly notebook documentation and provenance generated by distributed heterogeneous components.

OIntEd: online ontology instance editor enabling a new approach to ontology development

Ontology development involves people with different background knowledge and expertise. It is an elaborate process, where sophisticated tools for experienced knowledge engineers are available. However, domain experts need simple tools that they can use to focus on ontology instantiation. In this paper, we propose a methodology with a separation of concern between domain experts and knowledge engineers. This separation allows domain experts to focus on information processing and ontology instantiation while providing immediate feedback to the knowledge engineers on usability of the ontology being developed. We have designed and implemented OINTED, an adaptive online ontology instance editor that supports this methodology. We present usage examples of OINTED that highlight three main features: the intuitive visualization of concepts, instances, and relationships within an ontology; the seamless integration in pre‐existing problem solving environment; and the assistance in ontology evolution. OINTED complements existing tools suited for knowledge engineers by enabling immediate feedback and a shorter ontology development life cycle. Copyright

Planning Data Intensive Workflows on Inter-domain Resources Using the Network Service Interface (NSI)

The recent emergence of advanced network infrastructures for e-Science enables tuning of network performance at the application level. The Network Service Interface (NSI) has been created as a result of collaborative development of network and application engineers primarily associated with the Research and Education (R&E) community. The NSI allows workflow systems not only to check available service points for a workflow engine to schedule executions, but also to reserve and provision network connections among those service points. However, the current NSI services are proposed mainly from the network resource management perspective, which concerns little about the programming model of applications. In this paper we extend our previous system called NEtWork QoS Planner (NEWQoSPlanner) by adding inter domain network resource selection and provisioning using NSI. We will discuss how NEWQoSPlanner invokes network services to achieve dynamic resource optimization for workflows, and how to apply such planner in heterogeneous infrastructures.