An electronic laboratory Notebook (ELN) can be characterized as a system that allows scientists to capture the data and resources used in performing scientific experiments. This allows users to easily organize and find their data however, little information about the scientific process is recorded. In this paper we highlight the current status of progress toward semantic representation of science in ELNs.

1. Toward Semantic Representation
of Science in Electronic Laboratory
Notebooks (ELNs)
Stuart J. Chalk
Department of Chemistry, University of North Florida
schalk@unf.edu
CINF Paper 50 – 251st ACS Meeting Spring 2016
#ACSCINFDataSummit

2.  Utopia: A Global Research Network
 What is an Electronic Notebook?
 The Semantics of Semantics
 What Needs to be Semantically Represented?
 Current lay of the land
 ELN Item Manifest
 P-PLAN Ontology
 VIVO-ISF Ontology
 Chemical Analysis Metadata Platform
 HCLS Community Profiles
 Electronic Notebook Ontology
 A generic scientific data model
 Experimental information for LD (ExptLD)
 Take Home
 Conclusion
Outline

3.  “Big Data” and the “Semantic Web” are the current buzz
words du jour but what do they mean for chemistry?
 Lots of heterogeneous data and metadata with even more
“semantic” data to represent it
 Look at what we want rather that what we have…
 We went chemical data that is:
 Easy to share, find, and compare
 Freely available but with provenance
 Globally sourced and without IP restrictions on reuse
Utopia: A Global Research Network

4.  An electronic way to record data…
 ...equivalent to a laboratory notebook
 But ELN’s should not be thought of so lowly...
 An ELN must:*
 Keep track of research data
 Reference resources used in research and…
 …capture the story of research
What is an
Electronic Laboratory Notebook?
* Insight from Tony Williams

5.  The interface should mirror a laboratory notebook
 Behind the scenes though it should use state of the art
software, data formats, data/metadata practices, and web
technologies to manage data generation, workflows,
remote data access, authentication etc…
 As a result it needs to speak the same language as other
data sources and store data in a format that others can read
and reuse
 Foundational building block of a Global Research Network
What should an ELN be?

6.  Semantics is the study of meaning
-> We need to give meaning to what is created in an ELN
 Described in computers using the Resource Description
Framework (RDF) which:
 Makes statements about objects…
 … their relationships to other objects...
 ...using subject-predicate-object “triples”
 RDF allows knowledge representation
 Meaning is represented by using one or more ontologies
The Semantics of Semantics

7. RDF in JSON-LD
{
"@context": {
"name": "http://schema.org/name",
"isAlive": "http://example.org/isAlive",
"age": "http://example.org/age",
"height": "http://schema.org/height",
"@base": "http://www.unf.edu/chemistry/stuart_chalk.aspx"
},
"@id": "",
"name": "Stuart Chalk",
"isAlive": true,
"age": 49,
"height": 188.0
}
http://json-ld.org/playground/

8. <http://www.unf.edu/chemistry/stuart_chalk.aspx>
<http://example.org/age>
"49"^^<http://www.w3.org/2001/XMLSchema#integer> .
<http://www.unf.edu/chemistry/stuart_chalk.aspx>
<http://example.org/isAlive>
"true"^^<http://www.w3.org/2001/XMLSchema#boolean> .
<http://www.unf.edu/chemistry/stuart_chalk.aspx>
<http://schema.org/height>
"188"^^<http://www.w3.org/2001/XMLSchema#integer> .
<http://www.unf.edu/chemistry/stuart_chalk.aspx>
<http://schema.org/name>
"Stuart Chalk" .
RDF in JSON-LD

9.  Everything!
 What areas?
 Data, Results and Resources
 Models, Tools for Data Workup (Equations, Tests, Stats)
 General Workflows (Protocols and Procedures)
 The Research Story (What, Why, How)
 User discussion and annotation
 ELN usage timeline
 The Science (Area, Hypotheses, Theories)
 The People (Expertise, Provenance, Integrity, Eminence)
What Needs to be
Semantically Represented?

11.  The P-PLAN Ontology
http://purl.org/net/p-plan
Workflows
Implement in Kepler, Taverna, Knime?

12. People: The VIVO-ISF Ontology
https://wiki.duraspace.org/download/attachments/51052811/PeopleOrgsRolesGrants.2014-03-14.png

13.  The Chemical Analysis Metadata Platform (ChAMP)
http://champ-project.org/
 Identification of metadata related to chemical
analysis and definition of an ontology to describe
terms
 Examples in both XML and JSON-LD with associate
XML Schema and JSON-LD context
 Journal Article
 Standard Method of Analysis
 Reference Material
The Science: ChAMP (an example)

14. ChAMP

15. ChAMP

16.  The Healthcare and Life Science (HCLS) Community Profile
is a Note from the Semantic Web HCLS Interest Group
 Access to consistent, high-quality metadata is critical to finding,
understanding, and reusing scientific data. This document
describes a consensus among participating stakeholders in the
Health Care and the Life Sciences domain on the description of
datasets using the Resource Description Framework (RDF). This
specification meets key functional requirements, reuses existing
vocabularies to the extent that it is possible, and addresses
elements of data description, versioning, provenance,
discovery, exchange, query, and retrieval.
Data Descriptions:
HCLS Community Profile
http://www.w3.org/TR/hcls-dataset/

17.  Describes three levels for
description of datasets
 Summary Level
 Type declaration (rdf:type =
dctypes:Dataset)
 Title (dct:title = rdf:langString)
 Description (dct:description =
rdf:langString)
 Publisher (dct:publisher = IRI)
 Version Level
 Type declaration (rdf:type =
dctypes:Dataset)
 Title (dct:title = rdf:langString)
 Description (dct:description =
rdf:langString)
 Creator (dct:creator = IRI)
 Publisher (dct:publisher = IRI)
 Version identifier (pav:version =
xsd:string)
 Version linking (dct:isVersionOf = IRI)
 Distribution Level
 Type declaration (rdf:type =
void:Dataset OR dcat:Distribution)
 Title (dct:title = rdf:langString)
 Description (dct:description =
rdf:langString)
 Creator (dct:creator = IRI)
 Publisher (dct:publisher = IRI)
 License (rdf:type = IRI)
Data Descriptions:
HCLS Community Profile
http://www.w3.org/TR/hcls-dataset/#datasetdescriptionlevels

18. Electronic Notebook Ontology (ENO)

19. ENO

20. ENO

21.  Use a Generic
Scientific Data
Model
 Captures data
and metadata
about datasets
and links to
related data
 JSON-LD is
ideal file format
Data and
Resources

22.  A specification (written in XML) that describes
different data types of information recorded during
the scientific process (http://exptml.sourceforge.net
Experiment Markup Language (ExptML)
 Sample
 Solution
 Space
 Specimen
 Substance
 Task
 Template
 Timeline
 User
 Vendor
 Annotation
 Api
 Calculation
 Chemical
 Citation
 Communication
 Customer
 Data
 Dataset
 Definition
 Element
 Equipment
 Event
 Experiment
 Group
 Project
 Protocol
 Quote
 Report
 Result

23. Experimental Linked Data (ExptLD)
 Define data packets
that capture the
metadata of
 Resources
 Data
 Integrate with other
ExptLD packets to
create a SciData
document
 Or convert to RDF and
store in a triplestore

24.  A lot exists to semantically represent the scientific process
that can be leveraged as part of an ELN system
 A data standard needs to be agreed upon
 Agreeing on implementation standards will take time
because of size of user community
 Integration and coverage of ontologies will be necessary to
fully implement a system that underpins a Global Research
Network
 Domain specific knowledge representation needed in many
areas
Take Home

25.  schalk@unf.edu
 Phone: 904-620-1938
 Skype: stuartchalk
 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?