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Tech. session : Interoperability and Data FAIRness emerges from a novel combination of Web technologies

The document discusses the principles of FAIR data (Findable, Accessible, Interoperable, Reusable) and proposes a solution using 'fair accessors' for publishing metadata about various scholarly entities in a machine-actionable format. It emphasizes the importance of existing standards over new APIs for achieving interoperability and describes practical applications of fair accessors in supporting reproducibility and transparency in research data management. Additionally, it introduces related concepts such as Triple Pattern Fragments (TPF) and Resource Mapping Language (RML) for integrating data from non-FAIR sources.

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In a FAIR world my paper is the supplementary information for my publication
Mark D. Wilkinson CBGP-UPM/INIA, Madrid markw@illuminae.com FAIRness emerges from a novel combination of Web technologies OAI10, Geneva, June 2017 http://tinyurl.com/WilkinsonOAI10
The Problem We surveyed 100 datasets associated with nonmolecular studies ... 64% were archived in a way that partially or entirely prevented reuse. “ ” Dominique G. Roche , Loeske E. B. Kruuk, Robert Lanfear, Sandra A. Binning (2015) http://dx.doi.org/10.1371/journal.pbio.1002295
The Problem Is that data, therefore... Useless?
The Problem NO...
The Problem It’s Reuseless!  h.t. to Barend Mons
FAIR Findable → Globally unique, resolvable, and persistent identifiers → Machine-actionable contextual information supporting discovery Accessible → Clearly-defined access protocol → Clearly-defined rules for authorization/authentication Interoperable → Use shared vocabularies and/or ontologies → Syntactically and semantically machine-accessible format Reusable → Be compliant with the F, A, and I Principles → Contextual information, allowing proper interpretation → Rich provenance information facilitating accurate citation The Four Principles
FAIR Findable → Globally unique, resolvable, and persistent identifiers → Machine-actionable contextual information supporting discovery Accessible → Clearly-defined access protocol → Clearly-defined rules for authorization/authentication Interoperable → Use shared vocabularies and/or ontologies → Syntactically and semantically machine-accessible format Reusable → Be compliant with the F, A, and I Principles → Contextual information, allowing proper interpretation → Rich provenance information facilitating accurate citation The Four Principles
“Skunkworks” Task: Build a prototype
Skunkworks Participants Mark Wilkinson Michel Dumontier Barend Mons Tim Clark Jun Zhao Paolo Ciccarese Paul Groth Erik van Mulligen Luiz Olavo Bonino da Silva Santos Matthew Gamble Carole Goble Joël Kuiper Morris Swertz Erik Schultes Erik Schultes Mercè Crosas Adrian Garcia Philip Durbin Jeffrey Grethe Katy Wolstencroft Sudeshna Das M. Emily Merrill
The Hourglass Concept We want a large ecosystem of apps that use FAIR Data
The Hourglass Concept We want to support a wide range of source providers
The Hourglass Concept The FAIR solution between them must be THIN!
Keeping the history brief A series of teleconferences led to the concept of putting metadata into an iterative set of ~identical “containers”
Just say NO to APIs! We also decided to reject any solution that required a new API ProgrammableWeb.com already catalogues >16,000 different Web APIs
Just say NO to APIs! ProgrammableWeb.com already catalogues >16,000 different Web APIs APIs DO NOT MAKE YOU INTEROPERABLE! We also decided to reject any solution that required a new API
Just say NO to APIs!
Are there existing standards that are And have the properties of
The FAIR Accessor In incremental detail
What can we describe with FAIR Accessors? FAIR Accessors provide a machine-actionable, structured, REST-oriented way to publish Metadata about a wide range of scholarly “entities”
What can we describe with FAIR Accessors? Warehouses (e.g. EBI) Databases (e.g. UniProt) Repositories (e.g. Zenodo, INRA-URGI Wheat Repo, UniProt) Datasets (e.g. output from a workflow) Research Objects (data a/o workflow a/o results a/o publications) Data “slices” (e.g. the result of a database query) Data Records (e.g. image, excel file, patient clinical record) Other…
HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Container Resource
“Resource” is a URI / URL HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”?
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”?
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? There is a URI for the “Container” (of any of the kinds listed in the previous slide)
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? The only HTTP method we currently use is HTTP GET
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? What is returned is a document full of metadata richly describing that Container (warehouse, database, dataset, slice, etc.) And a list of Resources (URIs) that represent the contained “things”
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? Looking more closely at one of those contained things...
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? The contained thing is a Resource
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? That Resource can be resolved by HTTP GET
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? To retrieve a Metadata document describing that resource (e.g. a single record)
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Which record does this Metadata describe? The foaf:primaryTopic attribute defines this
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Using the metadata structures defined by DCAT the FAIR Accessor may also tell you how to get the content of the record, and what formats are available
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? In this case, the record is available in XML format By calling HTTP GET on URL_U2
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Or in RDF format by calling HTTP GET on URL_U1
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”?
Or you may add additional layers... Metadata Metadata Metadata Metadata DATA - format 1 DATA - format 2
Features of the FAIR Accessor 1: There is no API GET Interpret the Metadata Select the desired Resource GET
Features of the FAIR Accessor 1: There is no API GET Interpret the Metadata Select the desired Resource GET ANY Web agent can explore/index a FAIR Accessor (e.g. Google) An agent that understands globally-accepted vocabularies can explore it “intelligently”
Features of the FAIR Accessor 2: Identifiers for unidentifi-ed/-able things HTTP GET <FAIR metadata/> This is the ArrayExpress query I did for paper doi:10/1234.56 Results: MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... Should assist with reproducibility and transparency
Features of the FAIR Accessor 3: A predictable “place” for metadata PrimaryTopic: record 1A445 Record Metadata... DATA - format 1 DATA - format 2 Different “kinds” of metadata have distinct ontological types, and distinct document structures. There is no ambiguity regarding what kind of thing the metadata is describing. Dataset metadata MetaRecordURL
Features of the FAIR Accessor 3: Symmetry & predictable path to citation XXX Part of dataset XXX Metadata... DATA - format 1 DATA - format 2 The record metadata contains an “upward” link to the Repository- level metadata, which should contain (additional) license and citation information Dataset metadata: Cite: doi:10/8847.384 License: cc-by
Features of the FAIR Accessor 4: Granularity of Access/Privacy/Security Container Resource HTTP GET <FAIR metadata/> Contains <<184 Records>> Contact Mark Wilkinson For more information about These records
Features of the FAIR Accessor 4: Granularity of Access/Privacy/Security Thin solution - if it’s private, say nothing!
The Real Thing A working FAIR Accessor Serving a “Slice” of UniProt
A real-world scenario... You are publishing a paper describing the evolution of proteins in the RNA Processing machineries of the fungus Aspergillus nidulans. You want to be a good scholarly publisher interested in transparency and reproducibility So you must describe, in detail, the inclusion/exclusion criteria for selecting proteins for your dataset (today, this is generally done either in the text of the paper, or not at all...)
Create and publish a FAIR Accessor for that query http://linkeddata.systems/Accessors/UniProtAccessor Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
Create and publish a FAIR Accessor for that query http://linkeddata.systems/Accessors/UniProtAccessor Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... Resolve the URI (in software or in your browser)
Create and publish a FAIR Accessor for that query Returns a page of metadata (in this example, in RDF) Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
52
53 Note that this Metadata is about ME! I am the creator of this dataset, and may be credited for it.
54 The query (i.e. inclusion criteria)
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET Step down to individual Record metadata
Step down to individual Record metadata MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET Software calls HTTP GET on the URL representing the MetaRecord Resource for the desired record in the Container (or just click on it, or type it into your browser)
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml The document that is returned
Note the change in metadata focus! This metadata is about the UniProt Record (not about Mark Wilkinson). The record described in this metadata was created by UniProt, so the citation and authorship information is now THEIRS, not MINE.
Container Resource Symmetrical Link back upward to the Accessor Container, for additional metadata
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml
Two ways to retrieve the record - RDF or HTML (in REST-speak, two Representations of that Resource)
Note that this metadata record is somewhat more FAIR, than what you can (easily) retrieve from UniProt itself! e.g. the UniProt record does not include the citation or license information - you have to manually surf around the UniProt Web page to find that. So the Accessor makes UniProt’s already notably FAIR data, even more FAIR (with respect to “R”)
So far, we have focused on FAIR Metadata
Are there approaches to making the DATA FAIR?
FAIR Projection: Providing FAIR Data from non-FAIR Data Dynamically
Imagine the data we need to integrate is in a CSV file in FigShare or Zenodo How do we discover and integrate that data?
Triple Pattern Fragments + RDF Mapping Language Ruben Verborgh Ghent University Anastasia Dimou Ghent University
Triple Pattern Fragments (TPF) A REST approach to requesting/retrieving RDF Triples from any source Ruben Verborgh “Slices” of data, from any source, are considered Resources and are therefore represented by a distinct URL: http://some.database.org/dataset?s=___;p=___;o=___ Calling HTTP GET on a TPF URL returns the set of Triples matching {?s, ?p, ?o} PLUS hypermedia instructions and Resource URLs for other relevant slices.
Triple Pattern Fragments (TPF) A REST interface for retrieving RDF Triples (from any source) Ruben Verborgh For example, the “BMI” column from a patient registry is a Resource with the URL: http://my.registry.org/patients?p=CMO:0000105 (CMO:0000105 = “body mass index””) HTTP GET gives me all BMI triples in the registry, together with other Resource URLs representing other “slices” that might be useful, for example: http://my.registry.org/patients?p=CMO:0000004 (CMO:0000004 = “systolic B.P.”)
RML A way to describe the structure of an RDF document Anastasia Dimou RML allows us to create models of (meta)data structures “What could this data look like, if it were mapped to RDF?” RML fulfills similar objectives to DCAT Profiles, the Dublin Core Application Profile, and ISO 11179 - Metadata Registries; but has added advantages http://rml.io/RMLmappingLanguage.html
Using RML to describe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” T H E M O D E L
Using RML to describe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” T H E M O D E L We call this a Triple Descriptor These are used to describe the structure/semantics of data slices consisting of a set of “alike” triples
T H E M O D E L Using RML to describe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” Patient:123 rdf:type ex:Patient Record snp: rs0020394 ex:hasVariant rdf:type ex:SNP Example of Data
Where are we now? TPF - A standard, RESTful way to request Triples Triple Descriptors - A standard way to describe the structure and meaning of a Triple
Where are we now? TPF - A standard, RESTful way to request Triples Triple Descriptors - A standard way to describe the structure and meaning of a Triple We need a way to associate these with each other We need a way to associate these with a dataset or record
We already have that...
MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET The FAIR Accessor can do this Using the metadata structures defined by DCAT the FAIR Accessor also tells you how to get the content of the record, and what formats are available
If we consider the TPF URL to be just another DCAT Distribution, we get... <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml If we consider the TPF URL to be just another DCAT Distribution, we get... URL representing the Triple Pattern Fragment Resource
If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPFrag_URL_1 format rdf+xml Model: Triple_Desc_URL <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL_1 Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor HTTP GET on that URL returns:
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor Record + TPF Server + RML Model
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor FAIR Projector
If we consider the TPF Resource URL to be just another DCAT Distribution, we get… now add the Triple Descriptor HTTP GET on TPF_URL returns rdf+xml triples from Record R That look like Data interoperability <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL
<FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL How/why does this return Triples? We still have not defined a way to GENERATE these triples
Sadly, there is no magic wand to create interoperability
Sadly, there is no magic wand to create interoperability Someone has to write the TPF server that converts the data Interoperability will never come “for free” (because semantics will never come “for free”)
However, there are reasons for optimism! 1. Researchers transform data anyway to integrate 2. For the most common file formats (e.g. CSV or Excel), there are RML-based tools to automate the RDF transformation; simply create an RML model of what you want, and ask the tool to covert the file. 3. Investing time into creating an RML model is more FAIR than ad hoc “re-useless” brute-force transformation. When you create a FAIR Projector for your own data transformation needs, the model is reusable!
However, there are reasons for optimism! AND 4. RML Triple Descriptors are very simple (one triple!) so we can also templatize their construction  creating a FAIR Projector is quite easy in many cases! 5. Micro-attribution & citations FAIR Accessors/Projectors are FAIR objects - You can get credit if other people use your Projector for their analyses
Summary of FAIR Projectors FAIR Projectors provide a discoverable and standardized REST interface to retrieve interoperable data, and its interoperable metadataF+I+R A + I I FAIR Projectors convert non-FAIR data into FAIR data, or can change the structure, URL format, or semantics of existing FAIR data sources FAIR Projectors can be deployed over, and provide a common interface to: - Static Data Deposits, in any format, anywhere - Databases - Triplestores - Certain (common) types of Web Services R+++ Triple Descriptors are FAIR entities, intended for reuse, & None of this required a new API
Thanks to: Michel Dumontier - Stanford Center for Biomedical Informatics Research, Stanford, California. Ruben Verborgh – Ghent University – imec, Ghent, Belgium Luiz Olavo Bonino da Silva Santos - Dutch Techcentre for Life Sciences, Utrecht, The Netherlands - Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. Tim Clark - Department of Neurology, Massachusetts General Hospital Boston MA and Harvard Medical School, Boston, MA, USA Morris A. Swertz - Genomics Coordination Center and Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands Fleur D.L. Kelpin - Genomics Coordination Center and Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands Alasdair J. G. Gray - Department of Computer Science, School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK Erik A. Schultes - Department of Human Genetics, Leiden University Medical Center, The Netherlands Erik M. van Mulligen - Department of Medical Informatics, Erasmus University Medical Center Rotterdam, The Netherlands Paolo Ciccarese - Perkin Elmer Innovation Lab, Cambridge MA and Harvard Medical School, Boston MA, USA Mark Thompson - Leiden University Medical Center, Leiden, The Netherlands Jerven T. Bolleman - Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
In a FAIR world my paper is the supplementary information for my publication
Funding for Mark Wilkinson from: Fundacion BBVA and the UPM Isaac Peral programme, and the Spanish Ministerio de Economía y Competitividad grant number TIN2014-55993-R. Additional support for FAIR Skunkworks members comes from: European Union funded projects ELIXIR-EXCELERATE (H2020 no. 676559), ADOPT BBMRI-ERIC (H2020 no. 676550) CORBEL (H2020 no. 654248) Netherlands Organisation for Scientific Research (Odex4all project) Stichting Topconsortium voor Kennis en Innovatie High Tech Systemen en Materialen (FAIRdICT project) BBMRI-NL RD-Connect and ELIXIR (Rare disease implementation study FP7 no. 305444).
You are not only welcome to share and reuse this presentation... ...You are encouraged to! http://tinyurl.com/WilkinsonOAI10
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Tech. session : Interoperability and Data FAIRness emerges from a novel combination of Web technologies

  • 1.
    In a FAIRworld my paper is the supplementary information for my publication
  • 2.
    Mark D. Wilkinson CBGP-UPM/INIA,Madrid markw@illuminae.com FAIRness emerges from a novel combination of Web technologies OAI10, Geneva, June 2017 http://tinyurl.com/WilkinsonOAI10
  • 3.
    The Problem We surveyed100 datasets associated with nonmolecular studies ... 64% were archived in a way that partially or entirely prevented reuse. “ ” Dominique G. Roche , Loeske E. B. Kruuk, Robert Lanfear, Sandra A. Binning (2015) http://dx.doi.org/10.1371/journal.pbio.1002295
  • 4.
    The Problem Is thatdata, therefore... Useless?
  • 5.
  • 6.
  • 7.
    FAIR Findable → Globally unique,resolvable, and persistent identifiers → Machine-actionable contextual information supporting discovery Accessible → Clearly-defined access protocol → Clearly-defined rules for authorization/authentication Interoperable → Use shared vocabularies and/or ontologies → Syntactically and semantically machine-accessible format Reusable → Be compliant with the F, A, and I Principles → Contextual information, allowing proper interpretation → Rich provenance information facilitating accurate citation The Four Principles
  • 8.
    FAIR Findable → Globally unique,resolvable, and persistent identifiers → Machine-actionable contextual information supporting discovery Accessible → Clearly-defined access protocol → Clearly-defined rules for authorization/authentication Interoperable → Use shared vocabularies and/or ontologies → Syntactically and semantically machine-accessible format Reusable → Be compliant with the F, A, and I Principles → Contextual information, allowing proper interpretation → Rich provenance information facilitating accurate citation The Four Principles
  • 9.
  • 10.
    Skunkworks Participants Mark Wilkinson MichelDumontier Barend Mons Tim Clark Jun Zhao Paolo Ciccarese Paul Groth Erik van Mulligen Luiz Olavo Bonino da Silva Santos Matthew Gamble Carole Goble Joël Kuiper Morris Swertz Erik Schultes Erik Schultes Mercè Crosas Adrian Garcia Philip Durbin Jeffrey Grethe Katy Wolstencroft Sudeshna Das M. Emily Merrill
  • 11.
    The Hourglass Concept Wewant a large ecosystem of apps that use FAIR Data
  • 12.
    The Hourglass Concept Wewant to support a wide range of source providers
  • 13.
    The Hourglass Concept TheFAIR solution between them must be THIN!
  • 14.
    Keeping the historybrief A series of teleconferences led to the concept of putting metadata into an iterative set of ~identical “containers”
  • 15.
    Just say NOto APIs! We also decided to reject any solution that required a new API ProgrammableWeb.com already catalogues >16,000 different Web APIs
  • 16.
    Just say NOto APIs! ProgrammableWeb.com already catalogues >16,000 different Web APIs APIs DO NOT MAKE YOU INTEROPERABLE! We also decided to reject any solution that required a new API
  • 17.
    Just say NOto APIs!
  • 18.
    Are there existingstandards that are And have the properties of
  • 21.
    The FAIR Accessor Inincremental detail
  • 22.
    What can wedescribe with FAIR Accessors? FAIR Accessors provide a machine-actionable, structured, REST-oriented way to publish Metadata about a wide range of scholarly “entities”
  • 23.
    What can wedescribe with FAIR Accessors? Warehouses (e.g. EBI) Databases (e.g. UniProt) Repositories (e.g. Zenodo, INRA-URGI Wheat Repo, UniProt) Datasets (e.g. output from a workflow) Research Objects (data a/o workflow a/o results a/o publications) Data “slices” (e.g. the result of a database query) Data Records (e.g. image, excel file, patient clinical record) Other…
  • 24.
    HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIRmetadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Container Resource
  • 25.
    “Resource” is a URI /URL HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”?
  • 26.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”?
  • 27.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? There is a URI for the “Container” (of any of the kinds listed in the previous slide)
  • 28.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? The only HTTP method we currently use is HTTP GET
  • 29.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? What is returned is a document full of metadata richly describing that Container (warehouse, database, dataset, slice, etc.) And a list of Resources (URIs) that represent the contained “things”
  • 30.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... What does a FAIR Accessor “look like”? Looking more closely at one of those contained things...
  • 31.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? The contained thing is a Resource
  • 32.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? That Resource can be resolved by HTTP GET
  • 33.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? To retrieve a Metadata document describing that resource (e.g. a single record)
  • 34.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Which record does this Metadata describe? The foaf:primaryTopic attribute defines this
  • 35.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Using the metadata structures defined by DCAT the FAIR Accessor may also tell you how to get the content of the record, and what formats are available
  • 36.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? In this case, the record is available in XML format By calling HTTP GET on URL_U2
  • 37.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”? Or in RDF format by calling HTTP GET on URL_U1
  • 38.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET What does a FAIR Accessor “look like”?
  • 39.
    Or you mayadd additional layers... Metadata Metadata Metadata Metadata DATA - format 1 DATA - format 2
  • 40.
    Features of theFAIR Accessor 1: There is no API GET Interpret the Metadata Select the desired Resource GET
  • 41.
    Features of theFAIR Accessor 1: There is no API GET Interpret the Metadata Select the desired Resource GET ANY Web agent can explore/index a FAIR Accessor (e.g. Google) An agent that understands globally-accepted vocabularies can explore it “intelligently”
  • 42.
    Features of theFAIR Accessor 2: Identifiers for unidentifi-ed/-able things HTTP GET <FAIR metadata/> This is the ArrayExpress query I did for paper doi:10/1234.56 Results: MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... Should assist with reproducibility and transparency
  • 43.
    Features of theFAIR Accessor 3: A predictable “place” for metadata PrimaryTopic: record 1A445 Record Metadata... DATA - format 1 DATA - format 2 Different “kinds” of metadata have distinct ontological types, and distinct document structures. There is no ambiguity regarding what kind of thing the metadata is describing. Dataset metadata MetaRecordURL
  • 44.
    Features of theFAIR Accessor 3: Symmetry & predictable path to citation XXX Part of dataset XXX Metadata... DATA - format 1 DATA - format 2 The record metadata contains an “upward” link to the Repository- level metadata, which should contain (additional) license and citation information Dataset metadata: Cite: doi:10/8847.384 License: cc-by
  • 45.
    Features of theFAIR Accessor 4: Granularity of Access/Privacy/Security Container Resource HTTP GET <FAIR metadata/> Contains <<184 Records>> Contact Mark Wilkinson For more information about These records
  • 46.
    Features of theFAIR Accessor 4: Granularity of Access/Privacy/Security Thin solution - if it’s private, say nothing!
  • 47.
    The Real Thing Aworking FAIR Accessor Serving a “Slice” of UniProt
  • 48.
    A real-world scenario... Youare publishing a paper describing the evolution of proteins in the RNA Processing machineries of the fungus Aspergillus nidulans. You want to be a good scholarly publisher interested in transparency and reproducibility So you must describe, in detail, the inclusion/exclusion criteria for selecting proteins for your dataset (today, this is generally done either in the text of the paper, or not at all...)
  • 49.
    Create and publisha FAIR Accessor for that query http://linkeddata.systems/Accessors/UniProtAccessor Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
  • 50.
    Create and publisha FAIR Accessor for that query http://linkeddata.systems/Accessors/UniProtAccessor Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... Resolve the URI (in software or in your browser)
  • 51.
    Create and publisha FAIR Accessor for that query Returns a page of metadata (in this example, in RDF) Container Resource HTTP GET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
  • 52.
  • 53.
    53 Note that thisMetadata is about ME! I am the creator of this dataset, and may be credited for it.
  • 54.
  • 59.
    Container Resource HTTPGET <FAIR metadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ...
  • 60.
    Container Resource HTTP GET <FAIRmetadata/> Contains MetaRecordResource1 MetaRecordResource2 MetaRecordResource3 ... MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET Step down to individual Record metadata
  • 61.
    Step down toindividual Record metadata MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET Software calls HTTP GET on the URL representing the MetaRecord Resource for the desired record in the Container (or just click on it, or type it into your browser)
  • 62.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml The document that is returned
  • 64.
    Note the changein metadata focus! This metadata is about the UniProt Record (not about Mark Wilkinson). The record described in this metadata was created by UniProt, so the citation and authorship information is now THEIRS, not MINE.
  • 65.
    Container Resource Symmetrical Link back upwardto the Accessor Container, for additional metadata
  • 66.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml
  • 67.
    Two ways toretrieve the record - RDF or HTML (in REST-speak, two Representations of that Resource)
  • 68.
    Note that thismetadata record is somewhat more FAIR, than what you can (easily) retrieve from UniProt itself! e.g. the UniProt record does not include the citation or license information - you have to manually surf around the UniProt Web page to find that. So the Accessor makes UniProt’s already notably FAIR data, even more FAIR (with respect to “R”)
  • 69.
    So far, wehave focused on FAIR Metadata
  • 70.
    Are there approachesto making the DATA FAIR?
  • 71.
    FAIR Projection: Providing FAIRData from non-FAIR Data Dynamically
  • 72.
    Imagine the data weneed to integrate is in a CSV file in FigShare or Zenodo How do we discover and integrate that data?
  • 73.
    Triple Pattern Fragments + RDFMapping Language Ruben Verborgh Ghent University Anastasia Dimou Ghent University
  • 74.
    Triple Pattern Fragments(TPF) A REST approach to requesting/retrieving RDF Triples from any source Ruben Verborgh “Slices” of data, from any source, are considered Resources and are therefore represented by a distinct URL: http://some.database.org/dataset?s=___;p=___;o=___ Calling HTTP GET on a TPF URL returns the set of Triples matching {?s, ?p, ?o} PLUS hypermedia instructions and Resource URLs for other relevant slices.
  • 75.
    Triple Pattern Fragments(TPF) A REST interface for retrieving RDF Triples (from any source) Ruben Verborgh For example, the “BMI” column from a patient registry is a Resource with the URL: http://my.registry.org/patients?p=CMO:0000105 (CMO:0000105 = “body mass index””) HTTP GET gives me all BMI triples in the registry, together with other Resource URLs representing other “slices” that might be useful, for example: http://my.registry.org/patients?p=CMO:0000004 (CMO:0000004 = “systolic B.P.”)
  • 76.
    RML A way todescribe the structure of an RDF document Anastasia Dimou RML allows us to create models of (meta)data structures “What could this data look like, if it were mapped to RDF?” RML fulfills similar objectives to DCAT Profiles, the Dublin Core Application Profile, and ISO 11179 - Metadata Registries; but has added advantages http://rml.io/RMLmappingLanguage.html
  • 77.
    Using RML todescribe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” T H E M O D E L
  • 78.
    Using RML todescribe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” T H E M O D E L We call this a Triple Descriptor These are used to describe the structure/semantics of data slices consisting of a set of “alike” triples
  • 79.
    T H E M O D E L Using RML todescribe the structure and semantics of one “kind of” Triple Map1 Predicate Object Map Subject Map Object Map ex:Patient Record subjectMap template “http://example.org/patient/{id}” predicate ex:has Variant Map2 Subject Map2 SO:0000694 (“SNP”) template “http://identifiers.org/dbsnp/{snp}” Patient:123 rdf:type ex:Patient Record snp: rs0020394 ex:hasVariant rdf:type ex:SNP Example of Data
  • 80.
    Where are wenow? TPF - A standard, RESTful way to request Triples Triple Descriptors - A standard way to describe the structure and meaning of a Triple
  • 81.
    Where are wenow? TPF - A standard, RESTful way to request Triples Triple Descriptors - A standard way to describe the structure and meaning of a Triple We need a way to associate these with each other We need a way to associate these with a dataset or record
  • 82.
  • 83.
    MetaRecord Resource3 <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml HTTP GET The FAIR Accessor can do this Using the metadata structures defined by DCAT the FAIR Accessor also tells you how to get the content of the record, and what formats are available
  • 84.
    If we considerthe TPF URL to be just another DCAT Distribution, we get... <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml
  • 85.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml If we consider the TPF URL to be just another DCAT Distribution, we get... URL representing the Triple Pattern Fragment Resource
  • 86.
    If we considerthe TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPFrag_URL_1 format rdf+xml Model: Triple_Desc_URL <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL
  • 87.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL_1 Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor HTTP GET on that URL returns:
  • 88.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor Record + TPF Server + RML Model
  • 89.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL If we consider the TPF URL to be just another DCAT Distribution, we get… now add the Triple Descriptor FAIR Projector
  • 90.
    If we considerthe TPF Resource URL to be just another DCAT Distribution, we get… now add the Triple Descriptor HTTP GET on TPF_URL returns rdf+xml triples from Record R That look like Data interoperability <FAIR metadata/> foaf:primaryTopic Record R dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL
  • 91.
    <FAIR metadata/> foaf:primaryTopic RecordR dcat:Distribution_1 Source URL_U1 format rdf+xml dcat:Distribution_2 Source URL_U2 format application/xml dcat:Distribution_3 Source TPF_URL Format rdf+xml Model: Triple_Desc_URL How/why does this return Triples? We still have not defined a way to GENERATE these triples
  • 92.
    Sadly, there isno magic wand to create interoperability
  • 93.
    Sadly, there isno magic wand to create interoperability Someone has to write the TPF server that converts the data Interoperability will never come “for free” (because semantics will never come “for free”)
  • 94.
    However, there arereasons for optimism! 1. Researchers transform data anyway to integrate 2. For the most common file formats (e.g. CSV or Excel), there are RML-based tools to automate the RDF transformation; simply create an RML model of what you want, and ask the tool to covert the file. 3. Investing time into creating an RML model is more FAIR than ad hoc “re-useless” brute-force transformation. When you create a FAIR Projector for your own data transformation needs, the model is reusable!
  • 95.
    However, there arereasons for optimism! AND 4. RML Triple Descriptors are very simple (one triple!) so we can also templatize their construction  creating a FAIR Projector is quite easy in many cases! 5. Micro-attribution & citations FAIR Accessors/Projectors are FAIR objects - You can get credit if other people use your Projector for their analyses
  • 96.
    Summary of FAIRProjectors FAIR Projectors provide a discoverable and standardized REST interface to retrieve interoperable data, and its interoperable metadataF+I+R A + I I FAIR Projectors convert non-FAIR data into FAIR data, or can change the structure, URL format, or semantics of existing FAIR data sources FAIR Projectors can be deployed over, and provide a common interface to: - Static Data Deposits, in any format, anywhere - Databases - Triplestores - Certain (common) types of Web Services R+++ Triple Descriptors are FAIR entities, intended for reuse, & None of this required a new API
  • 97.
    Thanks to: Michel Dumontier- Stanford Center for Biomedical Informatics Research, Stanford, California. Ruben Verborgh – Ghent University – imec, Ghent, Belgium Luiz Olavo Bonino da Silva Santos - Dutch Techcentre for Life Sciences, Utrecht, The Netherlands - Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. Tim Clark - Department of Neurology, Massachusetts General Hospital Boston MA and Harvard Medical School, Boston, MA, USA Morris A. Swertz - Genomics Coordination Center and Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands Fleur D.L. Kelpin - Genomics Coordination Center and Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands Alasdair J. G. Gray - Department of Computer Science, School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK Erik A. Schultes - Department of Human Genetics, Leiden University Medical Center, The Netherlands Erik M. van Mulligen - Department of Medical Informatics, Erasmus University Medical Center Rotterdam, The Netherlands Paolo Ciccarese - Perkin Elmer Innovation Lab, Cambridge MA and Harvard Medical School, Boston MA, USA Mark Thompson - Leiden University Medical Center, Leiden, The Netherlands Jerven T. Bolleman - Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland
  • 98.
    In a FAIRworld my paper is the supplementary information for my publication
  • 99.
    Funding for MarkWilkinson from: Fundacion BBVA and the UPM Isaac Peral programme, and the Spanish Ministerio de Economía y Competitividad grant number TIN2014-55993-R. Additional support for FAIR Skunkworks members comes from: European Union funded projects ELIXIR-EXCELERATE (H2020 no. 676559), ADOPT BBMRI-ERIC (H2020 no. 676550) CORBEL (H2020 no. 654248) Netherlands Organisation for Scientific Research (Odex4all project) Stichting Topconsortium voor Kennis en Innovatie High Tech Systemen en Materialen (FAIRdICT project) BBMRI-NL RD-Connect and ELIXIR (Rare disease implementation study FP7 no. 305444).
  • 100.
    You are notonly welcome to share and reuse this presentation... ...You are encouraged to! http://tinyurl.com/WilkinsonOAI10
  • 101.
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