Over the last few years we have seen a tremendous growth in various data repositories pushed and supported by funding bodies and various data preservation initiatives. As a result we have now a variety of scientific resources, combined into a broad network and indexed through the directories like BioSharing and re3data. Such network, while growing quickly, is still in early days of adopting semantic web standards and does not yet support deep data indexing and discoverability, leave alone that mechanisms of intellectual properties protection are as simple as making data public or private at best. The lack of standards and well defined models to describe a scientific information structure even further inhibits free information flow which is essential for scientific discovery. One of the most affected areas is not surprisingly materials sciences where due to the inherent complexity of the field of study the situation is even more severe. In this talk we present a chemistry information platform designed to support a variety of data formats along with metadata, sophisticated ways of collaboration and secure data exchanges. We will discuss challenges that we have faced developing such platform as well as solutions that we have came with.

1. Open Science Data Repository
The Platform for Materials Research
Spring ACS 2017, San Francisco, CA
Rick Zakharov1, Valery Tkachenko1, Alexandru Korotcov1, Igor Presniakov2, Stepan Kalmykov2
1. Science Data Software, Rockville, MD, United States.
2. Chemistry Department, Moscow State University, Moscow, Russian Federation.

2. Current scientific data trends
● Need to extract wisdom from vast amount of
data
● Research data to be more open
● More connected scientific instruments
● Many data formats but little help integrating
disparate data sources
● Collaborative metadata creation and curation
will lead to more discoverability, better search
● More data is captured including video, audio,
IoT devices

3. Introduction to Open Science Data Repository
● Cutting edge user experience
● Multiple formats, conversion between formats
● Advanced search and visualization capabilities
● Integration with machine learning tools
● Elastic and extensible architecture
● Open-source tools
● Deployment on premises, in cloud, or hybrid

4. OSDR, the big picture

5. We have been hard at work

6. Organize your data in a natural way.
● Now-natural folder
structure
● Organize your data into
collections
● You have an option to
download anything to
your local drive as long
as the security context
allows itc

7. Chemical processing
● Support for
chemical formats
● Automatic
processing and
visualization

8. OSDR - documents

9. Other formats

10. Convert between formats
● Integrated
format
transformation

11. OSDR - mapping and conversion

12. OSDR - import

13. OSDR - export

14. Predefined or custom metadata
Tagging
Attributes
Taxonomies
Ontologies
Metadata
Harvesting
Industry
Standards
Metadata

15. Collaborative data authoring and curation
● Datacite.org
support
● Other formats
● Audit trail
● Notifications

16. Extensive search options
● Search language
● Elasticsearch
technology
● Domain-specific
search modules
● Search ranking

17. Integration with machine learning
● Automated ML
pipeline
● Pre-built ML
modules
● Comparison
between different
ML algorithms
● NB, NN, RF, SVM, LR
● DNN

18. Integrations
● ORCID, social network login, OSDR login
● Citation
● DOI
● QR code
● Native integration with OSDR ELN
● Extensible data-source integration

19. Extensible micro-service based architecture

20. Micro-service
● Single responsibility
● Simple API
● One-pizza size team
● Independent development
● Independent deployment
and scaling
● Different services can be
implemented using
different technologies

21. Our development approach
● Git flow
● Involve community through
open source
● Containerization
● Leading practices in CI/CD
● Automated testing, rapid
development

22. Summary
● OSDR is a research data
platform
● Can handle specific use cases
via modules
● New modules are coming
● Involve the community
● Remove proprietary software
barriers
● Evolve and improve
continuously

23. Meet the Team
Alexandru Korotcov
Data Science
Rick Zakharov
Technology
Valery Tkachenko
Ideas and plumbing

24. Thank you!
Contact us:
info@scidatasoft.com
Slides:
https://www.slideshare.net/valerytkachenko16