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Data is at the heart of research. ¹ As put by my colleague Jenny Muilenburg, Data Management Librarian at the University of Washington, “The research is the data; the article is just the advertisement.” While admittedly understating the important roles of context, design, interpretation, and synthesis, this statement underscores the reality that, in data-driven research, data is the focal point around which other elements are arrayed. It is the data that are contextualized, gathered, interpreted, and synthesized. Even though raw data rarely appears in research articles, its presence is keenly felt throughout.

Through the emergence of online platforms, electronic databases, and individually maintained professional profiles in such virtual spaces as Google Scholar and ORCID, access to up-to-date published research and to archives of studies reaching back decades has never been easier or more far-reaching. However, this access also highlights the comparative inaccessibility of source data, the central component of research that may ultimately make a contribution to the field equal to or possibly greater than the summary report.

The American Psychological Association, to whose ethical guidelines the JRME adheres, provides clear guidance on data accessibility. “APA encourages the open sharing of data among qualified investigators. Authors are expected to comply promptly and in a spirit of cooperation with requests for data sharing from other researchers” (2010b, p. 12). More specifically stated:

After research results are published, psychologists do not withhold the data on which their conclusions are based from other competent professionals who seek to verify the substantive claims through reanalysis and who intend to use such data only for that purpose, provided that the confidentiality of the participants can be protected and unless legal rights concerning proprietary data preclude their release (American Psychological Association, 2010a, Standard 8.14).

According to APA standards, then, submission of a manuscript to and publication of an article in the JRME presumes that the data on which the report is based are available for examination, verification, and reanalysis.

Beyond maintaining data for these specific purposes, initiatives are underway in a variety of domains promoting open sharing of data among researchers and across borders (Contreras & Reichman, 2015). As an inherently global phenomenon, music teaching and learning may lend itself particularly well to the open exchange of data. The prospect of making a data set available to colleagues in the field admittedly may trigger an initial sense of apprehension. Researchers in music teaching and learning, many with substantial experience as elementary and secondary school educators, may be particularly attuned to protection of information, a result of years of managing gradebooks, educational plans, and other student records. With the attention rightly given to research participant confidentiality, the imperative to protect data from improper access and usage may seem to overshadow the equally strong imperative to maintain data records and make them available for subsequent scholarly investigations. It is, of course, the links between data and participants—the ability to identify specific participants from particular responses, recordings, demographic information, or the like—that must be kept confidential, not the data in its entirety.

APA guidelines suggest preserving data for “a minimum of five years after publication” (2010b, p. 12). However, the practicality and efficiency of electronic archiving, the emergence of retrospective methodologies such as meta-analysis, and the possibilities presented by a “commons” approach to scholarship (Frischmann, Madison, & Strandburg, 2014) point toward more long-term maintenance of data sets. Resources for data management, preservation, and distribution are readily available, however even basic steps taken during the data collection and entry process can facilitate access and use at a later time. First, future use of data requires clear understanding and communication of the definitions applied to the terminology, the way in which constructs were operationalized, the scale of measurement employed, and the manner in which the data were coded (Baskin, 2016). Making data decipherable through the use of clear descriptions or a detailed code key will ultimately benefit both other researchers who wish to verify or reanalyze older data and our future selves who, upon visiting our earlier work, will certainly have long forgotten overly idiosyncratic and enigmatic nomenclature systems. Second, the use of multiple storage sites (the cloud, an external hard drive) and basic file formats (.txt, .csv) will help protect against the certainty of obsolete hardware and defunct software (a floppy disc with a SuperANOVA spreadsheet? Oh, dear).

The JRME welcomes the inclusion of data sets among the supplementary materials connected with published articles. Likewise, within an article’s text it is possible for authors to include links to external data repositories. And the presence of contact information for one author from each published study implicitly invites other researchers to make inquiries pertaining to verification, replication, or reanalysis. The comparatively few pages inhabited by the studies appearing in each issue of the JRME represent only a portion of the valuable contribution to scholarship offered by this research.