A Metadata Model for Data Centric Security

Author(s):  
Benjmin Aziz ◽  
Shirley Crompton ◽  
Michael Wilson
Keyword(s):  
2003 ◽  
Vol 12 (03) ◽  
pp. 325-363 ◽  
Author(s):  
Joseph Fong ◽  
Qing Li ◽  
Shi-Ming Huang

Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.


2017 ◽  
Vol 6 (2) ◽  
pp. 50 ◽  
Author(s):  
Nengcheng Chen ◽  
Yingbing Liu ◽  
Jia Li ◽  
Zeqiang Chen

2011 ◽  
Vol 7 (1) ◽  
pp. 199-208 ◽  
Author(s):  
Gaetan Martens ◽  
Ruben Verborgh ◽  
Chris Poppe ◽  
Rik Van De Walle
Keyword(s):  

2010 ◽  
Vol 5 (1) ◽  
pp. 106-118 ◽  
Author(s):  
Brian Matthews ◽  
Shoaib Sufi ◽  
Damian Flannery ◽  
Laurent Lerusse ◽  
Tom Griffin ◽  
...  

In this paper, we present the Core Scientific Metadata Model (CSMD), a model for the representation of scientific study metadata developed within the Science & Technology Facilities Council (STFC) to represent the data generated from scientific facilities. The model has been developed to allow management of and access to the data resources of the facilities in a uniform way, although we believe that the model has wider application, especially in areas of “structural science” such as chemistry, materials science and earth sciences. We give some motivations behind the development of the model, and an overview of its major structural elements, centred on the notion of a scientific study formed by a collection of specific investigations. We give some details of the model, with the description of each investigation associated with a particular experiment on a sample generating data, and the associated data holdings are then mapped to the investigation with the appropriate parameters. We then go on to discuss the instantiation of the metadata model within a production quality data management infrastructure, the Information CATalogue (ICAT), which has been developed within STFC for use in large-scale photon and neutron sources. Finally, we give an overview of the relationship between CSMD, and other initiatives, and give some directions for future developments.    


Semantic Web ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 81-97
Author(s):  
Riccardo Albertoni ◽  
Antoine Isaac

The Data Quality Vocabulary (DQV) provides a metadata model for expressing data quality. DQV was developed by the Data on the Web Best Practice (DWBP) Working Group of the World Wide Web Consortium (W3C) between 2013 and 2017. This paper aims at providing a deeper understanding of DQV. It introduces its key design principles, components, and the main discussion points that have been raised in the process of designing it. The paper compares DQV with previous quality documentation vocabularies and demonstrates the early uptake of DQV by collecting tools, papers, projects that have exploited and extended DQV.


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