1. Why to submit your data and metadata?
Petra ten Hoopen, PhD
European Nucleotide Archive

2. Why to submit your data and metadata to public data archives?
Molecular data archives
Metadata importance
Reporting of environmental data and metadata
Support for data reporting

3. European Nucleotide Archive
1. Molecular data archives
European Nucleotide Archive
Permanent and comprehensive repository for public domain nucleotide sequences and associated information
Archiving
Helpdesk
Training
Standards development
Technology development
Community building

4. ENA 1. Molecular data archives ENA data flow raw reads assemblies
Direct presentation
Browser/Search/Download
ENA data flow
ENA
raw reads
assemblies
annotation
Large-scale
Programmatic services
ENA-captured data
validation
processing
archiving
Brokered data
Small-scale
WEBIN submission tool
INSDC-exchanged data
Infrastructure services
Domain-specific databases

5. 1. Molecular data archives
ENA data model
Data = reads and nucleotide sequence assemblies Metadata = information associated with sequences, includes provenance of biological sample (sample), sequencing experiment (experiment) and its scope (study), analysis and annotation of sequences (analysis), and files of raw data (run)
Study
Experiment
Analysis
Sample
Run
Data

6. ENA data standardization
1. Molecular data archives
ENA data standardization
Standardized reporting requirements for all metadata and data objects
Study
Experiment
Analysis
Sample
Run
Data
agreed by:
INSDC
Consortia of scientific domain-specific experts (e.g. GSC, MicroB3, RNACentral, GMI)
implemented with:
community-agreed checklists and control vocabularies, data-type-specific file formats

7. Metadata on sampling and experimentation are essential:
2. Metadata importance
metadata are data about data
Metadata on sampling and experimentation are essential:
what
where
when
who
how
Data without metadata are useless!

8. 2. Metadata importance - data discovery
Umbrella project with component sequencing projects

9. 2. Metadata importance – data discovery
free text search, sequence similarity search, programmatic access,
data download
advanced search

10. 2. Metadata importance - data discovery
mpling_platform=%22SV%20Tara%22%22&domain=sample

11. 2. Metadata importance – data comparison
If metadata is adequately described, using a standardised vocabulary, comparing sequencing projects becomes possible
Show the microbial species found in the North Pacific
… at depths of 50 – 100 m
… in samples taken May-June
… compared to the Indian Ocean, under the same conditions

12. Unified description of marine datasets
2. Metadata importance - data comparison
Unified description of marine datasets
Tara Oceans consortium
2009/2012 Tara Oceans, a global view
2013 Tara Oceans Polar Circle
Sampling route of the Tara Oceans expedition (Scientific Data 2, Article number: (2015)

13. Unified description of marine datasets
2. Metadata importance - data comparison
Unified description of marine datasets
OSD consortium
21st June 2014 Ocean Sampling Day
21st June 2015 Ocean Sampling Day
Map of OSD Sites (

14. 2. Metadata importance - data analysis
OSD Analysis Consortium (unpublished)
Selected InterPro families are enriched (or otherwise) corresponding to various environmental conditions. For instance the IPR001661is very much underrepresented at certain PAR value and IPR is overrepresented at certain latitude.
Heatmap of significant Spearman correlations between protein families and environmental conditions across 150 sites

15. 2. Metadata importance - data analysis
If metadata is adequately described, using a standardised vocabulary, comparing sequencing projects becomes possible

16. 3. Reporting environmental data and metadata
INSDC-agreed what should be reported and how
Genome Assembly (GA) – layers of reads, contigs, scaffolds, chromosome
Read Data (RD) – sequence reads, associated sequencing study/experiment/analysis
Feature Table (FT) – provenance and functional annotation of assembled sequences
Third Party Data (TPA) – (re)assembly/annotation of existing records by third party

17. 3. Reporting environmental data and metadata
community-developed what should be reported and how
MIGS, MIMS, MIMARKS (MIxS) – Minimum Information about any (x) Sequence
M2B3 – Minimum Information about marine microbial sample
GMI:MDM – Minimal Data for Mapping in relation to the Global Microbial Identifier pathogen tracking initiative
MINSEQE – Minimum Information about a high-throughput Nucleotide SeQuencing Experiment
BARCODE – biodiversity standard formulated by the Consortium for the Barcode of Life, CBOL currently approves as effective barcodes loci: cox1 (for animals), matK +rbcL (for plants) and ITS (for fungi)
GMI – standard for sequence data of genome-scale pathogen surveys in clinical, animal and environmental samples
MINSEQE – for description of high-throughput sequencing (HTS) experiments for unambiquous interpretation of HTS experiments

18. MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
3. Reporting environmental data and metadata
MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
Yilmaz et al., 2011

19. MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
3. Reporting environmental data and metadata
MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
Yilmaz et al., 2011

20. MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
3. Reporting environmental data and metadata
MIxS (MIGS, MIMS, MIMARKS) Minimum Information about any (x) Sequence
Example: MIMS-compliant water sample:
Submitted to INSDC
Project name
Investigation type
Sequencing method
Geographic location (latitude and longitude)
Geographic location (country and/or sea region)
Collection date
Environment (biome)
Environment (feature)
Environment (material)
Environmental package-water
Depth

21. MIxS CDI OBIS 3. Reporting environmental data and metadata M2B3
Minimum information about marine microbial sample
MIxS
CDI
OBIS
Multidisciplinary standard, new insight into marine ecosystem functioning and its biotechnological potential by relating marine microbial diversity with its environmental oceanographic context.
ten Hoopen et al. 2015

22. 3. Reporting environmental data and metadata
M2B3 Reporting Standard minimum information about marine microbial sampling

23. M2B3 MIxS 3. Reporting environmental data and metadata
Example: M2B3-compliant marine sample:
investigation campaign
investigation site
investigation platform
protocol label
sample title
geographic location (latitude and longitude)
collection date
depth
biome
feature
material
temperature
salinity
scientific name
taxon ID
parameter ID
Example: MIMS-compliant water sample:
submitted to INSDC
project name
investigation type
sequencing method
geographic location (latitude and longitude)
geographic location (country and/or sea region)
collection date
environment (biome)
environment (feature)
environment (material)
environmental package-water
depth

24. 3. Reporting environmental data and metadata
GMI
Minimum information about pathogen sample
collector name
collecting institution
collection date / receipt date
geographic location (latitude and longitude)
geographic location (country and/or sea region)
sample capture status (e.g. surveillance, farm)
isolate
pathogen testing no
yes
pathogen association
host name
host subject ID
host health state
host disease
isolation source host-associated
host sex/age/behaviour/habitat
host inoculation
isolation source non-host-associated
GMI for global identification of pathogens to detect outbreaks and new pathogens.
environmental sample no
yes
strain
serovar / serotype
human surveillance data
(antiviral treatment, vacciantion details, illness details)

25. 3. Reporting environmental data and metadata
How many ways can you say ‘male’
37 year old male
initial phase male
male fetus
six males mixed
600 yr. old male m
male plant
stallion
adult male
make
male, 8 weeks old
steer
bull
makle
male, castrated
sterile male
castrated male
mal e
male, pooled
strictly male cm
male
males
tetraploide male
dioecious male
male (7-2872)
man
type i males
diploid male
male (7-3074)
men
type ii males
drone
male (m-a)
normale male
virgin male
engorged male
male (m-o)
ram
winged and wingless males
fertile male
male caucasian
rooster
young male
four males mixed
male child
s1 male sterile
individual male
male fertile
sex: male
male (note: this sample was originally provided as a \female\ sample to us and therefore labeled this way in the brawand et al. paper and original geo submission; however, detailed data analyses carried out in the meantime clearly show that this sample stems from a male individual)

26. 3. Reporting environmental data and metadata
ENVO
Environment (biome) = broad ecological context
e.g. oceanic pelagic zone biome(ENVO: )
Environment (feature) = local environment determined by
e.g. marine surface current(ENVO: )
Environment (material) = surrounded by
e.g. saline water(ENVO: )

27. 3. Reporting environmental data and metadata
Null value reporting language
not collected – information has not been collected
not provided - not given, a value may be given at the later stage
restricted access - information exists but can not be released openly
not applicable - information is inappropriate to report
We strongly encourage to provide true values whenever possible!

28. 4. Support for data reporting
Sequencing study description in WEBIN submission tool
what, who
Study
Experiment
Analysis
Sample
Run
Data

29. 4. Support for data reporting
ENA Checklists for sample provenance description in WEBIN submission tool
where, when, how
MIxS microbial mat biofilm
MIxS host associated
MIxS human associated
MIxS human gut
MIxS human oral
MIxS human skin
MIxS human vaginal
MIxS plant associated
MIxS miscellaneous env.
MIxS sediment
MIxS soil
MIxS wastewater sludge
MIxS water
MIxS built env.
ENA default sample
ENA prokaryotic pathogen
GMI:MDM:1.1 pathogen
ENA virus pathogen
ENA Influenza
ENA M2B3 sample
ENA Tara sample
ENA plant sample
Study
Experiment
Analysis
Sample
Run
Data

30. 4. Support for data reporting
ENA Checklists for sample provenance description in WEBIN submission tool
Select checklist
Select fields
Fields values

31. 4. Support for data reporting
Controlled vocabularies for sequencing experiment description in WEBIN submission tool
how
Study
Experiment
Analysis
Sample
Run
Data

32. 4. Support for data reporting
Checklists for functional annotation in WEBIN submission tool
Select fields
Fields values
Study
Experiment
Analysis
Sample
Run
Data

33. Take home message Share your data to increase impact of your research
Data without metadata are useless
Describe your data as richly as you would like to find data of others
Use standardised descriptors
Use standardised values for descriptors
Keep data updated – archives present your data that give credits to you
Keep data updated – archives present YOUR data and the data give credits to YOU!

34. Thank you