1. Annotating All Knowledge
Overview of the Berlin Community Meeting
October 25, 2017

2. Berlin Community Meeting
Hosted by the CoKo Foundation and Hypothesis
Planned together with Europe PMC, ContentMine, PaperHive, and Pundit
Hackathon sponsored by Europe PMC

3. Berlin Community Meeting
Diversity
Reuse

4. Our Vision
Within three years, most scholarly works -- books, articles and other digital media, new and old -- will come with the capability for readers to create, share, and discover annotations from colleagues, authors, friends and experts around the globe.
This technology will be open source, federated, and based on open standards.
Just like the Web.

5. Our Plan
Partner with the world’s greatest platforms, publishers and libraries to design, deploy, and then curate an open annotation layer atop all digital books, articles and other online resources.

6. Annotating All Knowledge
hypothes.is/annotating-all-knowledge
Over 70 of the leading academic publishers, platforms and libraries are bringing web annotation to the world’s scholarship over the next several years.

7. Open annotation and its benefits
Annotation allows precision in citation and critique.
Web annotation technology is open source and based on an emerging web standard (w3.org/annotation).
Doesn’t need special hardware, just a browser and an Internet connection.
Group modes enable both private and public collaboration.
Supports a variety of formats like HTML, PDF, EPUB, and images.
Is a clear candidate for inclusion as an altmetric.

8. The ask Would you agree to the following?
We share the vision for how this can benefit scholarship.
We will explore how to incorporate web annotations into our [platform, publication, workflow, community].
We will collaborate openly with others in doing so.
You can mention our participation to others.

9. FAIR Annotations
Maryann Martone

10. The FAIR Guiding Principles for scientific data management and stewardship
High level principles to make data:
Findable
Accessible
Interoperable
Re-usable
Mark D. Wilkinson et al. The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data (2016). DOI: /sdata

11. FAIR and annotations? Annotations are data and should be FAIR
Annotations make data FAIR by adding searchable metadata and links

12. Findable
F1. (meta)data are assigned a globally unique and persistent identifier
F2. data are described with rich metadata
F3. metadata clearly and explicitly include the identifier of the data it describes
F4. (meta)data are registered or indexed in a searchable resource

13. Accessible
A1. (meta)data are retrievable by their identifier using a standardized communications protocol
A1.1 the protocol is open, free, and universally implementable
A1.2 the protocol allows for an authentication and authorization procedure, where necessary
A2. metadata are accessible, even when the data are no longer available

14. Interoperable
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles
I3. (meta)data include qualified references to other (meta)data

15. Re-usable
R1. meta(data) are richly described with a plurality of accurate and relevant attributes
R1.1. (meta)data are released with a clear and accessible data usage license
R1.2. (meta)data are associated with detailed provenance
R1.3. (meta)data meet domain-relevant community standards

16. Kick off Meeting: Force2016 in Portland
70+ attendees came together to:
Explore technical opportunities and challenges
Explore publisher’s opportunities and challenges
Converge on a definition of interoperability
Determine use cases that are in scope
Identify next steps

17. putting annotation fairness into practice
Francesca Di Donato
Maryann introduced us to the FAIR principles, (focusing on their declination to annotation).
There are many issues to be addressed, and I will start with a couple of examples based on my specific experience with Arts and Humanities scholars.You can consider these examples as use cases.
I work very often with teams of scholars. They create digital libraries where they publish critical editions. Their typical workflow is transcribing and encoding texts into TEI-XML and using Pundit to semantically annotate them.
2 recurrent elements I want to stress here:
First (not specifically related to annotation): they do not use the same workflow for their work! They compose their articles mainly as doc files, and export them in PDF for the publisher version. Taking no care at all about standards for data fairness and so one. The new technologies do not affect radically the way they work: more specifically, they don’t think about next scholars generations. Write in Word and convert to PDF. Stop. New technologies didn’t affected the way they work.
Second: very often, they ask us to have Pundit-made annotations back in the XML source document, again. So, the document is still seen as the “final product”. In such a way, they feel their work is more credited in this way.
There are many implications in both their behaviours, but I’d like to stress here is that data fairness concerns not only and not mainly technology and specific actions need to be implemented to change the way science is performed.

18. Main challenges
With this objective the GO FAIR initiative has been launched as a follow-up of the EOSC.

19. Main challenges
“The majority of the challenges to reach a functional European Open Science Cloud are social rather than technical”
*Realising the European Open Science Cloud. First report and recommendations of the Commission High Level Expert Group on the European Open Science Cloud

20. GO FAIR
GO FAIR is a bottom-up initiative to start working in a trusted environment where partners can deposit, find, access, exchange and reuse each other’s data, workflow and other research objects.
In practice, the GO FAIR implementation approach is based on three interactive processes/pillars:

21. GO-CHANGE GO-TRAIN GO-BUILD
The GO FAIR initiative
3 main processes:
GO-CHANGE
GO-TRAIN
GO-BUILD
Education/Training
MOOCs, SPOCs
Wizards
Certification
Culture change
Open Science promotion
Reward systems
Technical implementation
FAIR data and services
Technical infrastructure
The first pillar is go change: a cultural change is needed, where open science and the principles of data findability, interoperability, accessibility and reusability are a common way of conducting science.
The aim of the second pillar, go train, is to have core certified data experts and to have in each Member State and for each discipline at least one certified institute to support implementation of Data Stewardship per discipline.
The last pillar, go build, deals with the need for interoperable and federated data infrastructures and the harmonization of standards, protocols, and services, which enable all researchers to deposit access and analyse scientific data across disciplines.

22. GO FAIR Implementation Network on annotation
Possible actions
Communication
Advocacy
Training
Building
Hypothes.is, the Coalition and Pundit are supporting the creation of an implementation network on annotation:
in practice, it means adopting the go fair approach to establish 3 intertwining processes: Change, Train and Build.
Some actions could include the following activities:
Implement Website of the AAKC as a connecting point for federated events and initiatives.
Specific local but streamed initiatives of AAKC aiming at:
1) Changing research practices: call to ideas and brainstorming events on: annotation and (labelled) citations / annotation and peer reviewing (hypothes.is experiment) / annotation “status” - specific use cases; videolectures;
2) Training: webinars/MOOCs (such as OpenAire webinars)
3) Annual World event with local initiatives of FAIR annotation? (as in the case of the Open Access week).

23. Annotation for Literature Data Integration
Force 11
Berlin, October 24th 2017

24. Curation makes data FAIR
Deposition
Tools to assist reuse
Collaborative
enterprise, community standards
Citation, reproducibility
Analyse, curate and integrate
Classification
Share with other data providers

25. Data resources at EMBL-EBI
Literature & ontologies
Experimental Factor Ontology
Gene Ontology
BioStudies
Europe PMC
Chemical biology
ChEBI
ChEMBL
SureChEMBL
Molecular structures
Protein Data Bank in Europe
Electron Microscopy Data Bank
Gene, protein & metabolite expression
Expression Atlas
Metabolights
PRIDE
RNA Central
Protein sequences, families & motifs
InterPro
Pfam
UniProt
Genes, genomes & variation
Ensembl
Ensembl Genomes
GWAS Catalog
Metagenomics portal
Systems
BioModels
BioSamples
Enzyme Portal
IntAct
Reactome
Molecular Archives
European Nucleotide Archive
European Variation Archive
European Genome-phenome Archive
ArrayExpress

26. as a Platform Text and data mining community.
Providing deep links to data

27. ScliLite Annotations in Europe PMC

28. Linking annotations in SciLite
Link-out
Sentence level
Link-back

29. 2. Sharing automated annotations
Platform A
Curators
Platform B
Professional
Community Curation
Mapping
Triage
Feedback
Crosslinking
Annotations
Infrastructural components
Content
Engineering
Metadata

30. Annotations API API users can retrieve by
Annotation type (gene, disease, organism)
PMCID/PMID
Providers
Specific entity e.g. “heart attack” or “human”
CC-0, CC-BY, CC-BY-NC plus “OA subset”
Will be used in F11 Hackathon

31. Future Annotations Possibilities
Feedback on false negatives
Layering human annotations
Public
Groups such as curators (UX needed!)
Sharing annotations across different platforms
Co-development/co-outreach opportunities welcome!

32. Europe PMC is supported by:

33. Hi! Jennifer Lin, PhD Director of Product Management jlin@crossref.org
orcid.org/

34. FAIR is fair. Apply to annotations?
Discussion is critical for validation & reproducibility of results
Enable tracking of the evolution of scholarly claims through the lineage of expert discussion
Make reviews to the full history of the published results transparent
(Provide credit to contributors)

35. Annotations as publication metadata

36. Publishers: how to deposit
Directly into article’s metadata
as standard part of content registration process:
As part of references
AND/OR
As part of relations assertions (structured metadata)

37. But what if publisher is not aware?
Event Data collects activities surrounding publications with DOIs (nearly 100mil publications)
Annotations are important events!
Crossref Event Data event stream contains Hypothesis annotations right now. Interested in integrating more data sources.

38. Crossref & DataCite APIs
Event Data
Crossref & DataCite APIs

39. Making annotations fully FAIR
Annotations are important scholarly contributions & can be considered a form of peer review
Already being registered by some publishers but support is insufficient
NEW content type available dedicated to reviews (including pre- /post-pub annotations).
Register annotations (assign DOI) as content in Crossref
Through Event Data, track the online activity of annotations as autonomous/independent scholarly objects

40. Berlin Community Meeting
Annotations as part of workflow
Collaboration between Open Source Tool Providers
Business models and pathway to sustainability

41. Any questions? FAIR Panel: 10/26 at 10:30 in Galerie
Curathon: 12:00-1:30 Room 5
For more information on Annotating All Knowledge Coalition: or