Extending the data dictionary for data/knowledge management

Current relational database technology provides the means for efficiently storing and retrieving large amounts of data. By combining techniques learned from the field of artificial intelligence with this technology, it is possible to expand the capabilities of such systems. This paper suggests using the expanded domain concept, an object-oriented organization, and the storing of knowledge rules within the relational database as a solution to the unique problems associated with CAD/CAM and engineering data

Rdesign: A data dictionary with relational database design capabilities in Ada

Data Dictionary is defined to be the set of all data attributes, which describe data objects in terms of their intrinsic attributes, such as name, type, size, format and definition. It is recognized as the data base for the Information Resource Management, to facilitate understanding and communication about the relationship between systems applications and systems data usage and to help assist in achieving data independence by permitting systems applications to access data knowledge of the location or storage characteristics of the data in the system. A research and development effort to use Ada has produced a data dictionary with data base design capabilities. This project supports data specification and analysis and offers a choice of the relational, network, and hierarchical model for logical data based design. It provides a highly integrated set of analysis and design transformation tools which range from templates for data element definition, spreadsheet for defining functional dependencies, normalization, to logical design generator

PREMIS Data Dictionary for Preservation Metadata

The Repositories Support Project Briefing Paper on ‘Metadata’ examines how metadata standards can be used to make it easier to find, use and manage digital objects stored in an institutional repository. Long-term preservation of these objects can also be handled using metadata standards. This Web Advisory Document introduces The PREMIS Data Dictionary for Preservation Metadata, v2.02, the current authoritative metadata standard for digital preservation, and looks at how it can be used within an Institutional Repository

The Database Query Support Processor (QSP)

The number and diversity of databases available to users continues to increase dramatically. Currently, the trend is towards decentralized, client server architectures that (on the surface) are less expensive to acquire, operate, and maintain than information architectures based on centralized, monolithic mainframes. The database query support processor (QSP) effort evaluates the performance of a network level, heterogeneous database access capability. Air Force Material Command's Rome Laboratory has developed an approach, based on ANSI standard X3.138 - 1988, 'The Information Resource Dictionary System (IRDS)' to seamless access to heterogeneous databases based on extensions to data dictionary technology. To successfully query a decentralized information system, users must know what data are available from which source, or have the knowledge and system privileges necessary to find out this information. Privacy and security considerations prohibit free and open access to every information system in every network. Even in completely open systems, time required to locate relevant data (in systems of any appreciable size) would be better spent analyzing the data, assuming the original question was not forgotten. Extensions to data dictionary technology have the potential to more fully automate the search and retrieval for relevant data in a decentralized environment. Substantial amounts of time and money could be saved by not having to teach users what data resides in which systems and how to access each of those systems. Information describing data and how to get it could be removed from the application and placed in a dedicated repository where it belongs. The result simplified applications that are less brittle and less expensive to build and maintain. Software technology providing the required functionality is off the shelf. The key difficulty is in defining the metadata required to support the process. The database query support processor effort will provide quantitative data on the amount of effort required to implement an extended data dictionary at the network level, add new systems, adapt to changing user needs, and provide sound estimates on operations and maintenance costs and savings

2019-nCoV CRF data dictionary

Form used: nCoV_CRF_043020Last updated 2020May1data-dictionary.pdf2020762

2019-nCoV CRF data dictionary

CRf used: 03_2019-nCoV_Case Report Form 2020 0205_827pmLast updated 2020 0206_240pm2020722