This document discusses simple steps authors can take to make their research data more discoverable and reusable, including identifying the research organisms in the abstract, title and metadata, using unique identifiers for genes/gene products, making tables in publications available as text files, submitting data to appropriate repositories, and following FAIR data principles. Applying these practices will help researchers more easily find and utilize relevant data.

1. Discovering Discoverability
A Few Simple Things Authors Can Do to Make Their Data More Discoverable and Reusable
Leonore Reiser, Tanya Berardini, Donghui Li, and Eva Huala
The Arabidopsis Information Resource (TAIR) and Phoenix Bioinformatics contact: curator@arabidopsis.org
● The volume of published research in plant biology is large; each year, over 4000 research papers are indexed by PubMed about Arabidopsis alone.
● The querying power of bibliographic databases (and even Google) is limited, especially when key information is absent. Therefore researchers may have a hard time
finding relevant papers and data.
● Data curation and integration into public repositories makes research results more accessible to humans and machines.
● Biocurators can only extract and integrate a fraction of this experimental data-increasingly we need to rely on text mining but it is still quite error prone.
● Researchers can increase the visibility and re-usability of their research results by performing simple data curation tasks when they publish.
Identify your species
Include the identity of your research
organism(s) in your abstract, title and
metadata.This seems like a no brainer,
but sometimes this information is missing!
Especially if you used multiple
organisms.
Identify your bioentities
Use unique identifiers when describing
genes/gene products. Include
unambiguous identifiers such as
systematic locus or gene identifiers (e.g.
AT1G13750/GLYMA02G13070). Some
journals (e.g. Plant Cell, Plant Phys.)
require authors to list unique accessions
in a specific section.
Even if they don’t ask-- do it!
Unlock your tables
If you include data in tables make
sure there is a .csv, .tsv or similar
text file available. When tables are
included in PDFs (which are
sometimes saved as images) it
makes the information difficult to
access.
Submit your data!
Send your data to the appropriate
repository/database. Not sure where to
send it? Check out BioSharing
(biosharing.org) , publishers
recommendations, or contact a curator
from a representative database for your
research organism.
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Bonus Points!
● Learn about and apply FAIR
(Findable,Accessible, Interoperable, Reusable)
principles of data sharing.
● Include stock identifier(s) and the source. Even
better, submit your published seeds/clones to a
stock center or clone repository and include the
IDs in your paper.
● Before you start on a project, work out a data
management plan in consultation with database
biocurators to ensure data accessibility and
longevity.
References and Resources:
FAIR sharing principles(https://www.force11.org/fairprinciples)
Biosharing database (www.biosharing.org)
Dryad data repository (datadryad.org)
Leonelli,S., et al., (2017) Data management and best practice for plant science. Nature Plants (DOI: 10.1038/nplants.2017.86)
We are grateful for the support of our international community of TAIR subscribers and a grant from the Sloan Foundation
Example
PAP1 in Arabidopsis refers to:
AT1G13750 Purple Acid Phosphatase,
AT1G56650 Production of Anthocyanin
Pigment ,
AT2G01180 Phosphatidic Acid
Phosphatase,
AND AT3G16500 Phytochrome
Associated Protein
Include Metadata
Along with your data include metadata (data
about your data). Check with repositories to
identify appropriate metadata standards.
Use existing vocabularies/ontologies ( e.g.
Plant Ontology and Gene Ontology). Using
standard vocabularies helps make your data
more discoverable and interoperable.
Example
Minimal Information About Microarray Experiments
MIAME) http://www.fged.org/projects/miame/