Throughput:
Annotating Scientific Data

Collaborative Proposal

Simon Goring1; Doug Fils2; Eric C. Grimm3; Daisie Huang4; Stephen Kuehn5; Kerstin Lehnert6;
Nick McKay7; Amy Myrbo3; Anders Noren3; Steve Richard6; Jack Williams1

1University of Wisconsin - Madison, 2Ocean Leadership, 3University of Minnesota, 4Data Dryad, 5 Concord University,
6Lamont Doherty Earth Observatory, 7Northern Arizona University

Motivation

→ Information entropy ←


User question:

							A few of the calibrated chronologies have duplicate ages, for example Tower Lake:

							> A <- get_download(13047)
							> A[[1]]$chronologies$PalEON

							There is an entry for age 7091 ybp twice.

Expert response:

							Hi XXXXXXXXX, thanks for getting in touch.  In that case the result is fine, but I found an error in one of the other records that I've now corrected.  The reason for the duplicate there is that the author counted multiple samples from the same depth.

Science is Cultural

But Data is Shared

Key Elements

  • Standards survey & reporting
  • Cross-domain data mapping (tephra)
  • Secondary data capture - Annotation Engine

Data Standards in the Long Tail

  • Many ad hoc databases
  • Project-based, few informatics experts
  • User-focused - documentation needed

Cross-Domain Discovery

Annotation Engine

Annotations as Objects

Features

W3C Annotations using neo4j


rOpenSci Packages linked to GitHub Repositories

Features

OAuth2 management using ORCiD; API First Design