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.

Methods and systems for managing data created by different applications

Abstract: Systems and methods for managing data are provided. Data such as metadata from files created by several different software applications are captured, and the captured metadata is searched. The type of information in metadata for one type of file differs from the type of information in metadata for another type of file. A single search input is received and the search is performed through the metadata and content of the plurality of files and subset of the plurality of files stored on a user's data processing system. The search input is saved in a folder for performing future searches.

Metadata and the Future of Cataloging.

Abstract: This article is a survey of representative metadata efforts comparing them to MARC 21 metadata in order to determine if new electronic formats require the development of a new set of standards. This study surveys the ongoing metadata projects in order to identify what types of metadata exist and how they are used and also compares and analyzes selected metadata elements in an attempt to illustrate how they are related to MARC 21 metadata format elements.

Indexing multiple types of data to facilitate rapid re-indexing of one or more types of data

Abstract: A method and indexing system indexes the content of a body of documents into a content index, and the metadata of the documents into a metadata index which is a parallel index to the content index. The metadata is copied into a data store that is easily accessible by the indexing system and is stored in native form. The indexing system can dynamically re-index the metadata from the native metadata in the data store to produce a new metadata index which is used to replace the original metadata index. Search queries received by a search engine associated with the indexing system are applied to both the content and metadata index and the results are merged for return.

Towards an e-Infrastructure for urban research across Australia

Abstract: Australian urban and built environment research covers a multitude of research disciplines investigating social, economic and physical phenomena at a multitude of spatial and temporal scales and across diverse aggregation levels, from individual-level through to cohorts and populations, and across a range of scenarios, e.g. public health, voting patterns. The development of a common software platform (e-Infrastructure) to meet the needs of such research communities involves tackling many challenges associated with data intensive areas of research. This includes dealing with data sets from a multitude of federal, state, municipal, academic and private institutions, which hold vast arrays of heterogeneous data. For many researchers these data sets are difficult to discover, access, interrogate and use more generally. It is also unrealistic to expect researchers to always have the technical capability and capacity to handle such large amounts of data, or to develop data processing tools making use of such data sets, or be able to run computationally intensive simulations and models based on these data sets. Islands of expertise and islands (silos) of data currently exist that have fragmented urban research and thwarted a holistic approach to the study of the Australian urban and built environment system. The Australian Urban Research Infrastructure Network (AURIN - www.aurin.org.au) is a $20m SuperScience initiative established across Australia that seeks to address this directly by creating an e-Infrastructure aiming at bridging these gaps, by allowing researchers to conduct collaborative research in a security-enabled, browser-based environment providing seamless and transparent access to the distributed data and computational resources across Australia. These include metadata services, federated datasets, data integration and interrogation services, together with advanced visualization, collaboration and data storage capabilities. The goal is to provide access to rich datasets, state-of-the-art data processing tools, as well as a knowledge base where good research practices can be followed and used to assist researchers when navigating through vast data holdings to couple appropriate data and analytical tools for a range of urban research endeavors. In this paper, we address the fundamental question behind the establishment of this infrastructure, i.e. how to design a versatile and flexible software platform (e-Infrastructure) for urban research? The approach described is centered on establishment of a range of demonstrator projects addressing specific urban and built environment themes and the challenges they give rise to through a common e-Infrastructure. We believe that such an approach will allow delivery of early functionality in supporting a range of urban research scenarios, and at the same time support novel links between tools traditionally not applied beyond individual research fields. Through a common (core) e-Infrastructure, we expect to develop urban research capability that will offer a step change in how urban research is currently conducted, to support multi- and inter-disciplinary research scenarios whilst preserving full functionality in individual urban research strands. We describe the initial design stages of the AURIN e-Infrastructure from a technical perspective. The approach chosen is based on past experiences from a variety of eResearch initiatives, such as the UK e-Science National e-Infrastructure for Social Simulation (NeISS - www.neiss.org.au) project (Birkin et al., 2010); the Data Management through e-Social Science (DAMES - www.dames.org.au) project (McCafferty et al., 2009); the Spatial Information Software Stack (SISS) eResearch Facility (Liao et al., 2009), and the workflow-based image annotation using geographic information retrieval of TRIPOD (Purves et al., 2010). We illustrate the utility of the approach taken based on an initial set of demonstration projects exploring demographic and economic investigations of the Australian urban system.

Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories

Abstract: Data-driven approaches to scientific research have generated new types of repositories that provide scientists the means necessary to store, share and re-use big data-sets generated at various stages of the research process. As the number and heterogeneity of research data repositories increase, it becomes critical for scientists to solve data quality problems associated to the data-sets stored in these repositories. To date, several authors have been focused on the data quality issues associated to the data-sets stored in the repositories, yet there is little knowledge about the quality problems of the metadata used to describe these data-sets. Metadata is important for the long-term sustainability of research data repositories and data re-use. The aim of the research reported in this paper was to identify the data quality problems associated with the metadata used in the Dryad data repository. The paper concludes with some recommendations for improving the quality of metadata in research data repositories.