Presentations

Dataverse 4.0 UX , at Dataverse Community Meeting, Harvard University, Cambridge, MA 02138, Wednesday, June 10, 2015

Presented by: Elizabeth Quigley

An update on Dataverse, why a rewrite was done, and information on future collaborations. 

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Towards a Common Deposit API (Dataverse Example), at Dataverse Community Meeting Pre-Meeting Workshop, Harvard University, Cambridge, MA 02138, Tuesday, June 9, 2015

Presented by: Elizabeth Quigley and Phil Durbin.

For the past few years Dataverse has been using the SWORD protocol as the standard for a Data Deposit API, but is this the standard all repositories should use for Data Deposit APIs? We will discuss the good parts and the challenges of this approach. Additionally this presentation will lead into the Panel Discussion consisting of various stakeholders from publishers, domain and general repositories, funding agencies, researchers, and industry.

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Dataverse, a repository framework for all, at IASSIST 2015, Minneapolis, Minnesota, Friday, June 5, 2015

Since 2006, Dataverse, an open source data repository framework, is used at multiple institutions around the world to share, find, cite, and preserve research data. The Dataverse is for all, including individual researchers who need to make their datasets accessible to others, archives that need a framework to store and disseminate their data, academic institutions that need a repository to retain the data from their researchers, and publishers that need a public repository to make data accompanying a publication accessible to all. Some of these groups use public Dataverse...

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Increasing openness and connections throughout the scientific workflow, at IASSIST Data Conference, June 2-5, 2015, Minneapolis, MN, Wednesday, June 3, 2015

Presented by: Elizabeth Quigley

We can improve scientific communication to increase efficiency in the accumulation of knowledge. This requires at least two changes to the present culture.  One change is conceptual - embracing that progress is made more rapidly via identifying errors in current beliefs than by finding support for current beliefs.  Such a shift could reduce confirmation bias, unproductive theory testing, and the blinding desire to be right. The other change is practical - science will benefit from improving technologies to document and connect the entire...

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