Pattern-oriented software architecture: a system of patterns
Pattern-oriented software architecture: a system of patterns
Design and use of software architectures: adopting and evolving a product-line approach
Design and use of software architectures: adopting and evolving a product-line approach
The social science dream machine: resource discovery, analysis, and delivery on the web
Social Science Computer Review
A quantitative categorical analysis of metadata elements in image-applicable metadata schemas
Journal of the American Society for Information Science and Technology
IEEE Internet Computing
Software Engineering (7th Edition)
Software Engineering (7th Edition)
The data documentation initiative: the value and significance of a worldwide standard
Social Science Computer Review
A framework for information quality assessment
Journal of the American Society for Information Science and Technology
The DRIADE project: phased application profile development in support of open science
DCMI '07 Proceedings of the 2007 international conference on Dublin Core and Metadata Applications: application profiles: theory and practice
A conceptual framework for metadata quality assessment
DCMI '08 Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications
Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age
Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age
Institutional structures for research data and metadata curation
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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The proliferation of discipline-specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed-methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata-related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (0.6), a Fisher's exact test for nonparametric data was used to determine significance (p Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have “scheme harmonization” (compatibility and interoperability with related schemes) as an objective; schemes with the objective “abstraction” (a conceptual model exists separate from the technical implementation) also have the objective “sufficiency” (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective “data publication” do not have the objective “element refinement.” The analysis indicates that many metadata-driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata-related research, particularly in the context of recent funding agency policy changes. © 2012 Wiley Periodicals, Inc.