The IUPAC Solubility Data Series published its first volume in 1979. Since then over 100 volumes of high quality peer reviewed solubility data has been published, first in hardcopy and subsequently electronically as part of the Journal of Physical and Chemistry Reference Data. In February of this year the National Institute of Standards and Technology (NIST) funded a grant to explore taking the 18 currently available online volumes of data and re-purpose them as a REST based website, with documented API, and semantic representation/annotation. In this way the high quality data from these volumes can be shared, both to humans and computers. In addition, the semantic representation of the data allows integration of the data with other semantically enabled data at repositories across the globe. This presentation will give an overview of the process of schema development for the dataset, implementation in MySQL, website construction in the CakePHP framework, and architecture of the API access points. A report on the ontology development to support the project will also be discussed.

1. Sharing Science Data:
Semantically Reimagining the
IUPAC Solubility Series Data
Stuart J. Chalk
Department of Chemistry
University of North Florida
schalk@unf.edu
SCTY 132 - Pacifichem 2015

2.  Thoughts on Policy and Procedures
 Case in Point – the SDS
 Development Perspective
 The Scientific Data Model
 Database Structure for SDM
 Mapping NIST DB to SDM DB
 Current Status
 Management and Tools
 To Do List
 Acknowledgements
Overview
http://aspiresquared.co.uk/2011/01/metadata-what-is-its-purpose/

3.  Scientific publications need to be reimagined
 Describe work and highlight advancements yes! …
 ...but also provide access to original data as default
 For all reasearch (not just federally funded)
 With appropriate attribution/provenance…
 …and timestamp and digital signature
Thoughts on Policies and Procedures

4.  Implementation needs to be designed by scientists to
engage the community and get buy-in to change paradigm
 National societies need to promote good practices in digital
collection, annotation and reporting of scientific data …
 ... and mandate that it be taught as part of the curiculum in
chemistry!
 Don’t publish useful scientific data in ways you can’t use it!
Thoughts on Policies and Procedures

5. Case in Point…
 IUPAC Solubility Data Series
 1979-present 103 volumes
 Paper volumes until 1996 (up to volume 65)
 Electronic articles in JPCRD
 Abstracting solubility data from the literature by scientists,
careful reporting of values with context
 Great resource but why not electronic?

11.  Understanding the NIST SDS DB structure
 Migration strategy development
 Database migration (iterative)
 Scientific Data Model development and implementation
 UNF DB design
 Website development
 Ingest of chemical identifiers
 Identification of DOI’s for references
 Database cleanup
Activities

12.  A general model to describe/contain scientific data focuses
on the data not the view of the data
 Therefore, how the data is stored in a database should not
be governed by how the user views it
 Separating the view and the data structure a major focus
 Our perspective
 Systems (NIST DB) are two different views of SDS data
 Reports are a view of data from one reference about one or more
chemical systems
 Evaluations are an aggregated view of data from many reports
 Data in tables are aggregated views of data from reports and
optionally preparer/evaluator supplemental data
Development Perspective

13. Existing NIST DB Model

14. Scientific Data Model (SDM)

15. SDM
Database
Structure

16.  Each table has one to many rows
 Each row has one to many columns
 Data in a row is of different types
 Conditional Data – properties values that define context of data
 Experimental Data – the measured values in the paper
 Supplemental data (other property data)
 From the authors of the publication evaluated
 Calculated by the preparer or evaluator
 Notes
Interpreting Data in Tables

17. Interpreting Data in Tables
Conditional Data
Experimental Data
Supplemental Data

18. Interpreting Data in Tables

19.  All tables completely transferred except
 SOLDATA – 75% transferred
 SOLID_DATA – 50% transferred
 GAS_DATA, PARAMETERS_TB, FIGURES - not started
 TO DO’s
 Separate Evaluations from Reports
 Clean up and link references properly
 Get links to references that don’t have a DOI
 Additional integration into other API’s
 Write up API documentation
 Solubility Ontology
Current Status

20.  Project files are hosted on GitHub
 Collaborative environment
 Tracking issues
 Website (TO DO)
 Communication through Slack
 Integration with GitHub (issues and commits)
 PHP coding using PHPStorm
 Enforces coding standards, code checks, TO DOs
 GitHub (commits and issues) and MySQL
Management and Tools

21.  Finish the transfer of data!
 Replicate the current SRD website
 Standardize GUI using BootStrap CSS
 Check browser compatibility (NIST list of browsers?)
 Check for compliance with Section 508 for access
 Add exit script() for leaving NIST website
 Documentation
 PHP code, SDM schema, GUI, API
 Do roundtrip verification of the data
 New website will replace existing one by summer 2016
To Do List

22.  UNF
 Matthew Morse (UNF Senior)
 NIST SDS DB migration to UNF DB, SDM Testing
 Israel Hurst (UNF Junior)
 NIST SDS DB data transfer to UNF DB, UNF DB Cleanup
 John Turner (UNF Senior)
 Website implementation, UNF DB Cleanup
 NIST
 Bob Hanisch (ODI Director)
 Adam Morey, Peter Linstrom, Don Burgess, Angela Lee
Acknowledgements

23.  Interesting in knowing more about chemical data,
semantics and knowledge representation?
 251st American Chemical Society Meeting
San Diego, CA, USA March 13-17, 2016
 ACS Chemical Informatics Division “CINF Data Summit”
 All five days of the meeting three symposia
 "Tomayto vs. Tomahto: Overcoming Incompatibilities in Scientific Data”
 “Global Initiatives in Research Data Management & Discovery”
 “Chemistry, Data, & the Semantic Web: An Important Triple to Advance Science”
Shameless Plug

24.  schalk@unf.edu
 Phone: 904-620-5311
 Skype: stuartchalk
 Twitter: @StuChalk
 LinkedIn/Slidehare: https://www.linkedin.com/in/stuchalk
 ORCID: http://orcid.org/0000-0002-0703-7776
 ResearcherID: http://www.researcherid.com/rid/D-8577-2013
Questions?