Connecting Data Repositories with the Research Life Cycle

Since the Dataverse Project --an open source data publishing framework developed at Harvard's Institute for Quantitative Social Science-- released its SWORD API for data deposit in 2013, several stakeholders have developed integrations specifically into the Harvard Dataverse (<a href="https://dataverse.harvard.edu/" target="_blank">https://dataverse.harvard.edu/</a>) and other Dataverse-based repositories with various automated workflows throughout the research life cycle. This poster will demonstrate the technology necessary for interoperability between different systems with Dataverse, and highlight a number of these automated use cases which can occur at different times during the research lifecycle. Some examples include: researchers using R to deposit data and scripts into Dataverse (Dataverse R package on CRAN) or to archive data from a research project (OSF Dataverse Add-On); authors submitting data for a journal article (OJS and ScholarOne); and preserving research data for the long term using Archivematica

Citation++: Data citation, provenance, and documentationNew draft item

<p>The dawning of the digital research age –</p> <p>computational science, computational social</p> <p>science, and the digital humanities – brings</p> <p>with it both enormous potential and challenges.</p> <p>Visions of interactive publication,</p> <p>open data, reproducible results, and massive</p> <p>digital collections are exciting, opening</p> <p>up new research frontiers and the promise</p> <p>of more rapid dissemination of and building</p> <p>upon research ouput. However, to date,</p> <p>little of this vision has been realized. It remains</p> <p>challenging to reuse digital artifacts,</p> <p>precisely identify data used in a publication,</p> <p>and reproduce the results of published</p> <p>work. We leverage research in data citation</p> <p>and provenance collection and maintenance</p> <p>to prototype and evaluate a provenanceenabled</p> <p>citation service to facilitate better</p> <p>access to data sets and reproducibility of research</p> <p>results.</p

Survey results to question 2: Data sharing practices.

<p>Survey results to question: When it comes to sharing DATA you've created, collected or curated, you have?</p

Survey results to question 1: Data use practices.

<p>Survey results to question: Have you ever used DATA you learned about from reading a Journal article?</p

Volume of potential data links in astronomy publications.

<p>Total volume of external links in all articles published between 1997 and 2008 in the four main astronomy journals, color coded by HTTP status code. Green bars represent accessible links (200), grey bars represent broken links.</p

Distribution of survey respondents by year of doctoral graduation.

<p>Histogram representing respondents' year of Ph.D. completion (or expected). (n = 175).</p

Percentage of broken links in astronomy publications according to type of website.

<p>Percentages of broken external links in all articles published between 1997 and 2008 in the four main astronomy journals. Black circles represent links to personal websites (link values contain the tilde symbol, ^∼), while red crosses represent links to curated archives such as governmental and institutional repositories.</p

Data Publication and Dissemination with the Structural Biology Data Grid

<p>Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. In response to evolving needs of the structural biology community, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG, url: data.sbgrid.org), to preserve primary experimental datasets that support journal publications. Datasets archived with the SBDG are freely available to the research community under a public domain dedication license and the metadata for all datasets is published under the DataCite schema. Datasets are accessible to researchers through the Data Access Alliance infrastructure, which facilitates global and institutional data access. Our analysis of a pilot collection of crystallographic datasets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. It is anticipated that access to the experimental datasets will enable paradigm shift in the community from the static archive towards a much more dynamic body of continuously improving refined models. Following the success of this pilot study, the SBDG has extended its services to the entire community and will be used to develop support for other types of biomedical datasets, such as MicroED, Molecular Dynamics trajectories and LaPice Light-Sheet Microscopy.</p

Presentation Slides: New platforms and techniques for strengthening ties between observations and user communities.

Presentation Slides from the ESIP Summer Meeting 2017 Session: New platforms and techniques for strengthening ties between observations and user communities. <br>Thursday, July 27, 2017, 9-10:30am Bloomington, IN<br