1. Data Management: report & news.
PaNDaaS WG 2nd
12th of Dec 2016
Jean-François Perrin (ILL)

2. Experimental data management
Some Results: Dec 2012 – Dec 2016
Co-funded by the European Union :
PaNData-Europe Grant Agreement No
PaNData-ODI Grant Agreement No RI

3. What has been done so far?
2008 1st discussion on Data Policy (PaNData)
2011 “Open” DP published - 3 (max 5) years embargo
2012 1st experiment under DP
2013 complete set of Data Management Services available for users: search, access, annotate, archive, identify, publish, …
since then, communication with our users …

4. Data Policy revisited Open data & how to protect and credit our users?
Updates waiting for publication
Based on the PaNData framework
Open data & how to protect and credit our users?
The facility shall act as a custodian for the data.
All raw data will be curated in a well-defined format with a unique ID (DOI).
Metadata is captured automatically and resides either within the raw data files, and/or in an associated on-line catalogue.
Users can release or give access to their data at any time, by default access to raw data, the associated metadata and the analysis data is restricted to the experimental team for a period of 3 years. During the 2 next years data are available on request. Thereafter, they become publicly accessible.
The embargo period can be extended on requests to the direction.
Publication based on data must acknowledge the source of the data and cite its unique identifier (CC-BY licence).
Also apply for CRG beam time when they use the ILL data infrastructure.

5. Data portal Tailored to ILL needs
Provide access to data, meta-data, logs, DOIs landing page, …
Scientists can contact the experimental team
Tools for managing data authZ
Grant individual access
Release data at any time (non-reversible)
Tailored to ILL needs
User management of data access authorization.
Users could decide to publish (open access) their data, before the end of the embargo period.
Linked to DOIs.
Linked to experimental logs.
Linked to user annotation tool.
Linked with proposal system.
Download of data.
Full text search
Index all available information: Proposal, experimental report, data file annotation, publications, …

6. Data Portal results
TRL 8/9
3 data sets publicly released before end of the embargo
26 access granted to external scientists (peer-review)
0 requests to get access to datasets under embargo (at least through the portal)
data files downloaded (90% external users) concerning 376 unique datasets

7. DOIs Collaboration with DataCite/INIST
Linking data and people through ORCID/ResearcherID
Collaboration with
DataCite/INIST
Linking data with publications

8. DOIs communications
We ask our users to cite data sets using the reference section of their articles. 

9. Issue #1: Awareness of the scientists
This is still new for most of the scientists
“What are DOIs? What are you talking about?”
We (ILL/ISIS) currently feel a bit alone – need to reach critical mass. (ESRF, PSI, ESS … are joining)
We need more communication – mentoring – cultural change - education.
Need to fill the gap between what we hear in RDA-like meetings and the daily reality of the scientists.
Still need to convince the scientist that a change is happening regarding experimental data.

10. Issue #2: Difficulty to collect the articles exploiting the experimental data
Technical reason : DOIs in figures instead of references, partial citations …
No tools yet available to easily collect references
CrossRef cited by linking - currently only for article (vs data) publishers ? -, OpenAire.
This is a business for the publishers.
Difficulties to get metrics: how successful are we?
We have currently (Dec 2016) collected less than 50 peer reviewed article referencing the data DOI.
How many are we missing?
Need to access freely information for building metrics.

11. Text not in the reference section.
Not easily findable through most of search services (WoS, scopus, …)
Only findable through google scholar.

12. Cited in an image instead of …
Not findable at all

13. Data DOI vs article DOI
Should be the DOI of the article, instead of the one of the data.

14. Issue #3: time Time for understanding data & analyses
Time for writing articles
Time for publishing
On our side Time for explaining & convincing
This is by nature a long process, but seeing the level of investment needed, we need to convince, we need evidence of success urgently.

15. Results as of Dec 2016
TRL 8/9
The reference to Data sets in scientific articles, through DOIs, is recently improving.
Real interest of the publishers
More user feedback: “Why I don’t get a DOI for experiment XYZ?” %
Scientists name disambiguation:
378 Scientist “publication name”
184 Orcid
141 Researcherid

16. One more issue: other repositories in the middle.
Cite as
M. J. Roy. (2016). Contour method and neutron diffraction dataset to determine the weld fusion zone shape on residual stress in submerged arc welding [Data set]. Zenodo.
Instead of
WITHERS Philip J.; ISHIGAMI Atsushi; PIRLING Thilo; ROY Matthew and WALSH Joanna. (2014). The effect of weld bead shape on residual stress in novel low heat input welding of steel. Institut Laue-Langevin (ILL) doi: /ILL-DATA
 Need for analysis preservation and publication.
Licence ?

17. Data Analysis As a Service.

18. Data volume evolution
Evaluation of new detectors leading to permanent instruments starting from Dec 2016.
Moving to list mode (vs Histo)

19. Impacts of the data volume evolution
Example of the EXILL campaign
Storage (2 experiments = 70TB)
ILL archive capacity & performance
Users’ storage becoming almost impossible
Moving data
Today how to carry 40TB to 10 different labs?
Why carrying them?
Analysis
Almost impossible in most users’ labs with such data sets.
But
32 direct (h-index 4) peer reviewed articles published
2 Phd-thesis
10+ international conferences …
Our user community is heterogeneous and made of biologists, material physicists, ... They are very rarely coming from the HEP community, they are not used to such large volume of data and could not benefit from important IT support in their home lab.

20. Data analysis as a Service
TRL 3/4
The aim is to proposed to users to access analysis services (data, software, IT capacity and expertise) remotely using standard tools (ideally only web browser).
Typical workflow:
1) The user connects remotely using his web browser and its credentials (Federated IM)
2) Then select one of the experiment he has performed in the list.
3) he is then connected to a service where the necessary analysis applications have been installed and configured for accessing directly the experimental data.
4) If necessary he could receive help and support from facility expert, during the analysis.
5) Analysis data are published.
As of Dec 2016
Openstack testbeds
Evaluation of the management APIs
More resources to come … soon
FIM stands for Federated Identity Management, i.e. UmbrellaID.org

21. Homework by Andy top 3 data analysis applications …
LAMP, Mantid, Matlab through a private cloud + remote desktop
what services could the e-infrastructures provide ?
OpenAire/Datacite: help us to communicate, collect metrics of data usage
GEANT: Global AAI? Hybrid-Cloud?
EGI/EUDAT: ???
If we submit a new PANDAAS proposal … what to solve.
DaaS (volume and ease), analysis preservation, metrics
NX as an immediate, temporary (scalability?) solution

22. Contact:
Portal:
Policy:
PaNData Collaboration: