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In life sciences and medical research, many journals ask for a specific style.Unless someone asks you for a specific style, consistency is more important than choosing the right style.Valuable research data often are not captured, cited, or reused.
Institutional practices to assure stewardship of data are far less mature than are practices to sustain access to publications. The global edge represents the inherently international character of scientific scholarship.
All of these factors contribute to the complexity of data citation and attribution. Data practices, data exchange, and citation and attribution all must work effectively across political, institutional, and disciplinary boundaries.
Pick a popular style like Vancouver and use a citation manager to do your heavy lifting (although its always a good idea to double check! AMA (American Medical Assocation) Style is used for citing medical research.
It is the standard for journals published by the American Medical Association.
By now, all of us are familiar with the data deluge metaphor.
We are being drowned in data, much of which is runoff.MLA Style is used for humanities, especially for literary research. It is maintained by the National Library of Medicine.Citation managers help you organize and keep track of your references and generate bibliographies.Among the questions to be explored are what a community considers to be data, what data might be shared, what data should be shared, when data can be shared, and in what forms can data be shared?We will consider what approaches may be generic across disciplines and what practices may be field-specific. We have had standards for cataloging data files since the 1970s. Similarly, data archives have been promoting data citation practices for several decades. Several developments contribute to the renewed interest in data citation and attribution, all of which are topics of this Workshop.However, over this same period, very few journal editors required data citations, disciplines did not instill data citation as a fundamental practice of good research, granting agencies did not reward the data citations of applicants, tenure and reward committees did not recognize data citations in annual performance reviews, and researchers did not take responsibility for citing data sources. One is the growth in data volume relative to storage and analytic capacities.Fields such as astronomy, physics, and genomics are producing more data than investigators can investigate themselves.When viewed as research products, data deserve attribution similar to that of publications. Among the installed bases that influence data citation are Internet protocols, publishing practices, and library cataloging methods.Attribution, in turn, requires mechanisms for references to be made and citations to be received. At the social end, infrastructure is linked to conventions of practice-whether cataloging or data management-and learned as part of membership in a community (e.g., librarians or astronomers).Data have become a critical focus for scholarly communication, information management, and research policy.We cannot address the full array of these issues, fascinating though they may be.