Meta Data Services

About: Meta Data Services is a research topic. Over the lifetime, 2564 publications have been published within this topic receiving 40102 citations.

Metadata and Modeling Frameworks: The Object Modeling System Example

Abstract: The main motivation for the usage of modeling frameworks for environmental simulation software is to manage and simplify the interoperability of (loosely) coupled simulation components. Conventional approaches in collaboration are using an A pplication Programming Interface (API). Recent developments in simulation frameworks focus on introspect ing architectures for simulation components, where components become passively explored and integrated i n to the framework. Such solutions seem to be more flexible to support the framework evolution because c omponents are less tight to a specific framework API. The Object Modeling System (OMS) is an introspect ing simulation framework, which uses metadata in annotated components such as (i) spatial and temporal c nstraint specification, (ii) data annotation for variables and parameters to specify simulation related da ta like runtime constraints for range validation, unit conversion, or automated testing. The OMS utilizes m tadata annotation (i) at model construction time to support proper spatial and temporal model assembly (ii) a nd at model runtime to support proper data linkage. This paper will emphasize on metadata access to upport model linkage to simplify the development of simulation components for environmental scientists and will give application examples based on the Object Modeling System

Database and Metadata Support of a Web-Based Multimedia Digital Library for Medical Education

Abstract: Digital Libraries play an important role in education; they are beneficial to both instructors and students Many Web file-based course material systems have been built, but most of them do not have effective management mechanisms Instead, they often have broken links and do not support metadata To transfer these course materials from a file repository to an integrated and searchable educational digital library, database and metadata supports are needed In this paper, we report our design and implementation of a Web-based multimedia digital library for medical education with database and metadata support Our system is built on top of SQL Server, a relational database management system It adopts the Instructional Management System (IMS) standard for metadata representation and the National Library of Medicine's Medical Subject Heading controlled vocabulary to remove ambiguity and inconsistency in metadata definitions It includes a sophisticated search engine for both database content and metadata It also supports the IMS Content Packaging Specification for learning materials export and exchange

A scientific data extraction architecture using classified metadata

Abstract: Data extraction and information retrieval from a great volume of data set always is a tedious and difficult work. Therefore, an effective and efficient technology for searching for desired data becomes increasingly important. Since metadata with certain attributes may characterize data files, to extract data with the help of metadata can be expectably to simplify the work. Metadata Classification has been proposed to improve significantly the performance of scientific data extraction. In this paper, a scientific data extraction architecture based on the assistance of metadata classification mechanism is proposed. The architecture is built by utilizing mediator/wrapper architecture to develop a scientific data extracting system to help oceanographer analyzing ocean's ecology. The result of performance evaluation shows that the architecture with the help of metadata classification can extract user's desired data effectively and efficiently.

Replichard: Towards Tradeoff between Consistency and Performance for Metadata

Abstract: Metadata scalability is critical for distributed systems as the storage scale is growing rapidly. Because of the strict consistency requirement of metadata, many existing metadata services utilize a fundamentally unscalable design for the sake of easy management, while others provide improved scalability but lead to unacceptable latency and management complexity. Without delivering scalable performance, metadata will be the bottleneck of the entire system. Based on the observation that real file dependencies are few, and there are usually more idempotent than non-idempotent operations, we propose a practical strategy, Replichard, allowing a tradeoff between metadata consistency and scalable performance. Replichard provides metadata services through a cluster of metadata servers, in which a flexible consistency scheme is adopted: strict consistency for non-idempotent operations with dynamic write-lock sharding, and relaxed consistency with accuracy estimations of return values where consistency for idempotent requests is relaxed to achieve high throughput. Write-locks are dynamically created at subtree-level and designated to independent metadata servers in an application-oriented manner. A subtree metadata update that occurs on a particular server is replicated to all metadata servers conforming to the application "start-end" semantics, resulting in an eventually consistent namespace. An asynchronous notification mechanism is also devised to enable users to deal with potential stale reads from operations of relaxed consistency. A prototype was implemented based on HDFS, and the experimental results show promising scalability and performance for both micro benchmarks and various real-world applications written in Pig, Hive and MapReduce.

A Rule-Based Framework of Metadata Extraction from Scientific Papers

Abstract: Most scientific documents on the web are unstructured or semi-structured, and the automatic document metadata extraction process becomes an important task. This paper describes a framework for automatic metadata extraction from scientific papers. Based on a spatial and visual knowledge principle, our system can extract title, authors and abstract from scientific papers. We utilize format information such as font size and position to guide the metadata extraction process. The experiment results show that our system achieves a high accuracy in header metadata extraction which can effectively assist the automatic index creation for digital libraries.