Alexander Wöhrer

Novel mediator architectures for Grid information systems

Virtualization is one of the key features of the Grid. As data-intensive applications gain on importance, it becomes crucial for the success of the Grid to provide transparent access to distributed/heterogeneous data sources as well. In this paper, we describe our concepts to provide a Virtual Data Source (VDS) - a logically single homogeneous data source - on the Grid. Various data sources like relational/XML databases and comma separated value files can be combined via a Mapping Schema. By allowing to invoke user defined functions during the mediation a flexible way of resolving heterogeneities is provided. To show the feasibility of the developed concepts and elaborate the basis for a dynamic version they have been seamlessly integrated into OGSA-DAI to provide a non-proprietary, centralized and easy to integrate solution.

@neurIST: Infrastructure for Advanced Disease Management Through Integration of Heterogeneous Data, Computing, and Complex Processing Services

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the systems architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the systems ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

Towards an open service architecture for data mining on the grid

Across a wide variety of fields, huge datasets are being collected and accumulated at a dramatical pace. The datasets addressed by individual applications are very often heterogeneous and geographically distributed, and are used for collaboration by the communities of users, which are often large and also geographically distributed. There are major challenges involved in the efficient and reliable storage, fast processing, and extracting descriptive and predictive knowledge from this great mass of data. In this paper, we describe design principles and a service based software architecture of a novel infrastructure for distributed and high-performance data mining in Grid environments.

Grid-Enabled Non-Invasive Blood Glucose Measurement

Earth and life sciences are at the forefront to successfully include computational simulations and modeling. Medical applications are often mentioned as the killer applicationsfor the Grid. The complex methodology and models of Traditional Chinese Medicine offer different approaches to diagnose and treat a persons health condition than typical Western medicine. A possibility to make this often hidden knowledge explicit and available to a broader audience will result in mutual synergies for Western and Chinese medicine as well as improved patient care. This paper proposes the design and implementation of a method to accurately estimate blood glucose values using a novel non-invasive method based on electro-transformation measures in human body meridians. The framework used for this scientific computing collaboration, namely the China-Austria Data Grid (CADGrid) framework, provides an Intelligence Base offering commonly used models and algorithms as Web/Grid-Services. The controlled execution of the Non-Invasive Blood Glucose Measurement Service and the management of scientific data that arise from model execution can be seen as the first application on top of the CADGrid.

Mediators in the Architecture of Grid Information Systems

Across a wide variety of fields, huge datasets are being collected and accumulated at a dramatical pace. The datasets addressed by individual applica- tions are very often heterogeneous and geographically distributed. In this paper, we describe our extensions and improvements to the reference implementation of the OGSA-DAI Grid Data Service prototype in order to provide a Virtual Data Source - a clean abstraction of heterogeneous/distributed data for users and ap- plications. By picturing general applicable access scenarios we are showing the great need for such a Grid data mediation service as well as the compliance with important requirements of virtual data sources.

D/sup 3/G: novel approaches to data statistics, understanding and preprocessing on the grid

Relocating the code for data preprocessing (DPP) closer towards the data source is the overall task of the D/sup 3/G framework (data statistics, data understanding, data preprocessing on the grid), developed within a joint project of the University of Vienna, the Vienna University of Technology and the Czech Technical University. This paper presents the data service side architecture to gather data statistics on-the-fly and use them in remote DPP methods on query results as well as an approach to gather exact continuous data statistics for whole tables in a database on the grid. The performance results of our prototype implementation are showing low running costs for the continuous data statistics inside the database and also the feasibility of our proposed data service side functionality.

Data Life Cycle Management and Analytics Code Execution Strategies for the Breath Gas Analysis Domain

In this paper we present a novel dataspace-based support platform for the international breath gas analysis community, which consists of over 30 institutions world wide with rapidly expanding research studies in various application domains. The work discussed in this paper is mainly consolidated of two independently targeted frameworks: a data life cycle management framework for e-Science applications and a code execution framework handling multiple problem solving environments. The first is based on our previous work, in particular the e-Science Life Cycle Ontology, which traces semantics about procedures a researcher is conducting during the execution of a scientific study. Within the ABA-platform these two frameworks are integrated as complementary components aiming at enabling reproducibility of breath gas studies. We present the architecture of the ABA-platform, discuss its security concept and provide a performance evaluation of the first vertical prototype implementation. Our approach to provide a platform that supports both, the preservation of scientific studies as well as their reproducibility with integrated execution services represents a novel solution for e-Science applications, where data management and code execution services can be complementary utilized.

Modeling and optimizing large-scale data flows

Modern scientific collaborations require large-scale integration of various processes. Higher-level dataflow languages are used on top of parallel and distributed dataflow systems to enable faster data-intensive workflow programs development, their easier optimization, and more maintainable code. In this paper, we present the rationales, design, and application of the needed advanced support for modeling and optimizing data flows for data mining and integration processes. The optimization research and development is based on dataflow pre-execution modeling and extending the registry of process activities by advanced annotations. Additionally, the overall process from a dynamic model to a static model as input for the optimization algorithms is described. This novel approach is implemented within an advanced graphical user interface, called the Process Designer, in order to support semi-automatic optimization as well as within a dataflow execution platform, called the Gateway. It can be adapted to any dataflow language implementation. The Process Designer architecture based on modern (meta-)modeling concepts naturally supports validated transformations between external textual and internal graphical representations of the targeted dataflow language, and in this way significantly increases the productivity and robustness of the implementation processes.

Performance evaluation of webrowset implementations

The exchange format in Software-oriented Architectures is typically XML based and for relational data the WebRowSet format is most prominent. Our WebRowSet implementation is based on XML indexing. It features on-demand parsing keeping only a part of the complete XML document in main memory and allows forward and backward navigation. This paper evaluates our implementation against other available ones, SUN reference implementation and OGSA-DAI implementation focused on data sets integrated into grids, with respect to time and memory needed in order to process large WebRowSet files.

Inside the NIGM Grid Service: Implementation, Evaluation and Extension

Chinese and Western medicines have a different understanding and approach to life, health, and illness - joining their complementary work and support them by an advanced information technology could result in an improved health system. The Non-Invasive Blood Glucose Measurement (NIGM) Service is a grid based implementation of a novel non-invasive method for measuring human blood glucose values exploiting Chinese meridian theory. In this paper, we describe the implementation of the NIGM service in detail, present an initial performance evaluation and discuss an extension towards other non-invasive long term diabetic relevant measurement. Additionally, the adaption of the ontology-based Medical records Annotation Tool (MedAT) framework towards usage in NIGM trails is elaborated.