Requirements and Services for Metadata Management

Knowledge-intensive applications pose new challenges to metadata management, including distribution, access control, uniformity of access, and evolution in time. This paper identifies general requirements for metadata management and describes a simple model and service that focuses on RDF metadata to address these requirements.     

A formal semantics for the Taverna 2 workflow model

This paper presents a formal semantics for the Taverna 2 scientific workflow system. Taverna 2 is a successor to Taverna, an open-source workflow system broadly adopted within the e-science community worldwide. The new version improves upon the existing model in two main ways: (i) by adding support for data pipelining, which in turns enables input streams of indefinite length to be processed efficiently; and (ii) by providing new extensibility points that make it possible to add new operators to the workflow model. Consistent with previous work by some of the authors, we use trace semantics to describe the effect of workflow computations, and we show how they can be used to describe the new features in the Taverna 2 model.     

Interference from retrieval cues in Parkinson's disease.

Objective: Existing studies on memory interference in Parkinson's disease (PD) patients have provided mixed results and it is unknown whether PD patients have problems in overcoming interference from retrieval cues. We investigated this issue by using a part-list cuing paradigm. In this paradigm, after the study of a list of items, the presentation of some of these items as retrieval cues hinders the recall of the remaining ones. Method: We tested PD patients' (n = 19) and control participants' (n = 16) episodic memory in the presence and absence of part-list cues, using initial-letter probes, and following either weak or strong serial associative encoding of list items. Results: Both PD patients and control participants showed a comparable and significant part-list cuing effect after weak associative encoding (13% vs. 12% decrease in retrieval in part-list cuing vs. no part-list cuing -control- conditions in PD patients and control participants, respectively), denoting a similar effect of cue-driven interference in the two populations when a serial retrieval strategy is hard to develop. However, only PD patients showed a significant part-list cuing effect after strong associative encoding (20% vs. 5% decrease in retrieval in patients and controls, respectively). Conclusions: When encoding promotes the development of an effective serial retrieval strategy, the presentation of part-list cues has a specifically disruptive effect in PD patients. This indicates problems in strategic retrieval, probably related to PD patients' increased tendency to rely on external cues. Findings in control conditions suggest that less effective encoding may have contributed to PD patients' memory performance. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Improving Data Quality in Practice: A Case Study in the Italian Public Administration

Assessing and improving the quality of data stored in information systems are both important and difficult tasks. For an increasing number of companies that rely on information as one of their most important assets, enforcing high data quality levels represents a strategic investment aimed at preserving the value of those assets. For a public administration or a government, good data quality translates into good service and good relationships with the citizens. Achieving high quality standards, however, is a major task because of the variety of ways that errors might be introduced in a system, and the difficulty of correcting them in a systematic way. Problems with data quality tend to fall into two categories. The first category is related to inconsistency among systems such as format, syntax and semantic inconsistencies. The second category is related to inconsistency with reality as it is exemplified by missing, obsolete and incorrect data values and outliers.In this paper, we describe a real-life case study on assessing and improving the quality of the data in the Italian Public Administration. The domain of study is set on taxpayer's data maintained by the Italian Ministry of Finances. In this context, we provide the Administration with a quantitative reckoning of such specific problems as record duplication and address mismatch and obsolescence, we suggest a set of guidelines for setting precise quality improvement goals, and we illustrate analysis techniques for achieving those goals. Our guidelines emphasize the importance of data flow analysis and of the definition of measurable quality indicators. The quality indicators that we propose are generic and can be used to describe a variety of data quality problems, thus representing a possible reference framework for practitioners. Finally, we investigate ways to partially automate the analysis of the causes for poor data quality.     

TAPER: query-aware,partition-enhancement for large,heterogenous graphs

Graph partitioning has long been seen as a viable approach to addressing Graph DBMS scalability. A partitioning, however, may introduce extra query processing latency unless it is sensitive to a specific query workload, and optimised to minimise inter-partition traversals for that workload. Additionally, it should also be possible to incrementally adjust the partitioning in reaction to changes in the graph topology, the query workload, or both. Because of their complexity, current partitioning algorithms fall short of one or both of these requirements, as they are designed for offline use and as one-off operations. The TAPER system aims to address both requirements, whilst leveraging existing partitioning algorithms. TAPER takes any given initial partitioning as a starting point, and iteratively adjusts it by swapping chosen vertices across partitions, heuristically reducing the probability of inter-partition traversals for a given path queries workload. Iterations are inexpensive thanks to time and space optimisations in the underlying support data structures. We evaluate TAPER on two different large test graphs and over realistic query workloads. Our results indicate that, given a hash-based partitioning, TAPER reduces the number of inter-partition traversals by \(\sim \)80%; given an unweighted Metis partitioning, by \(\sim \)30%. These reductions are achieved within eight iterations and with the additional advantage of being workload-aware and usable online.     

A comparison of using Taverna and BPEL in building scientific workflows: the case of caGrid

When the emergence of ‘service‐oriented science,’ the need arises to orchestrate multiple services to facilitate scientific investigation—that is, to create ‘science workflows.’ We present here our findings in providing a workflow solution for the caGrid service‐based grid infrastructure. We choose BPEL and Taverna as candidates, and compare their usability in the lifecycle of a scientific workflow, including workflow composition, execution, and result analysis. Our experience shows that BPEL as an imperative language offers a comprehensive set of modeling primitives for workflows of all flavors; whereas Taverna offers a dataflow model and a more compact set of primitives that facilitates dataflow modeling and pipelined execution. We hope that this comparison study not only helps researchers to select a language or tool that meets their specific needs, but also offers some insight into how a workflow language and tool can fulfill the requirement of the scientific community. Copyright © 2009 John Wiley & Sons, Ltd.     

An overview of S-OGSA: A Reference Semantic Grid Architecture

The Grid's vision, of sharing diverse resources in a flexible, coordinated and secure manner through dynamic formation and disbanding of virtual communities, strongly depends on metadata. Currently, Grid metadata is generated and used in an ad hoc fashion, much of it buried in the Grid middleware's code libraries and database schemas. This ad hoc expression and use of metadata causes chronic dependency on human intervention during the operation of Grid machinery, leading to systems which are brittle when faced with frequent syntactic changes in resource coordination and sharing protocols.The Semantic Grid is an extension of the Grid in which rich resource metadata is exposed and handled explicitly, and shared and managed via Grid protocols. The layering of an explicit semantic infrastructure over the Grid Infrastructure potentially leads to increased interoperability and greater flexibility.In recent years, several projects have embraced the Semantic Grid vision. However, the Semantic Grid lacks a Reference Architecture or any kind of systematic framework for designing Semantic Grid components or applications. The Open Grid Service Architecture (OGSA) aims to define a core set of capabilities and behaviours for Grid systems. We propose a Reference Architecture that extends OGSA to support the explicit handling of semantics, and defines the associated knowledge services to support a spectrum of service capabilities. Guided by a set of design principles, Semantic-OGSA (S-OGSA) defines a model, the capabilities and the mechanisms for the Semantic Grid.We conclude by highlighting the commonalities and differences that the proposed architecture has with respect to other Grid frameworks.     

Java call control, coordination, and transactions

Future telecommunications networks will consist of integrated packet-switched (IP and/or ATM), circuit-switched (PSTN), and wireless networks. Service providers will offer a wide portfolio of innovative applications over these integrated networks. Doing so rapidly and efficiently requires open network APIs, with a key API being that for call control, as well as for coordination and transactions. The JAIN community is defining an API for Java call control and Java coordination and transactions. The JCC API defines the interface for applications to initiate and manipulate calls, while JCAT defines the facilities for applications to be invoked and return results before or during calls. Note that in this context a call refers to a multimedia, multiparty, multiprotocol communications session. The JCC/JCAT Edit Group of JAIN is in the process of defining the first version of the JCC/JCAT API specification, which is expected to be released in early 2000. This article describes the background of and motivation for the design of the JCC/JCAT API. We describe the AIN and JTAPI call models on which the JCC/JCAT API is based. We then describe the scope of JCC/JCAT and its relationship to other JAIN Edit Groups defining facilities for enabling service creation. Finally, we describe the requirements and example service drivers for JCC/JCAT, as well as the initial proposed design and structure for JCC and JCAT