DASH

What is DASH?

A central, open-access repository of research by members of the Harvard community.

Deposit Your Work

DASH enlarges the audience and impact of your work. Authors who deposit in DASH have access to on-demand metrics and receive monthly reports about their readership. Deposited works receive persistent URLs, are comprehensively indexed by search engines, including Google and Google Scholar, reach academic and non-academic readers who may not have access to the original publications, and are preserved by the Harvard Library.

Making your work open access in DASH is as simple as completing our quick submit form. We also welcome bulk deposits and offer CV scraping services. Simply contact OSC if you are interested. OSC will do the legal legwork for all submissions.

The OSC is pleased to offer a robust suite of services to support you and your scholarship. Visit our For Authors page to learn more.

 

  • Increased H2CO production in the outer disk around HD 163296 

    Carney, M; Hogerheijde, M; Loomis, R; Salinas, Victoria; Oberg, Karin; Qi, C; Wilner, David (EDP Sciences, 2017-09)
    Context: The gas and dust in circumstellar disks provide the raw materials to form planets. The study of organic molecules and their building blocks in such disks offers insight into the origin of the prebiotic environment ...
  • The Behavioral and Neural Basis of Empathic Blame 

    Patil, Indrajeet; Calo, Marta; Fornasier, Federico; Cushman, Fiery; Silani, Giorgia (Center for Open Science, 2017-12-11)
    Mature moral judgments rely both on a perpetrator’s intent to cause harm, and also on the actual harm caused–even when unintended. Much prior research asks how intent information is represented neurally, but little asks ...
  • Comparison of Full and Empirical Bayes Approaches for Inferring Sea-Level Changes From Tide-Gauge Data 

    Piecuch, Christopher; Huybers, Peter; Tingley, Martin (American Geophysical Union (AGU), 2017-03)
    Tide‐gauge data are one of the longest instrumental records of the ocean, but these data can be noisy, gappy, and biased. Previous studies have used empirical Bayes methods to infer the sea‐level field from tide‐gauge ...

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