V.2.4. Allotrope Use Case. Heiner Oberkampf, PhD June 29 th 2018, Brussels EC NMBP Workshop on a European Materials Ontology

Transcription

1 V.2.4 Allotrope Use Case Heiner Oberkampf, PhD June 29 th 2018, Brussels EC NMBP Workshop on a European Materials Ontology

2 Laboratory Analytical Process sample analytical process data Slide 2

3 Allotrope Structure 2018 Astrix Technology Group BSSN Software Elemental Machines Erasmus MC Fraunhofer IPA The HDF Group LabAnswer LabWare Mettler Toledo NIST SciBite Stanford University University of Illinois at Chicago University of Southampton Slide 3 More information:

4 APIs (Java &.NET class libraries) Allotrope Data Format (ADF): A Universal Data Container Allotrope Data Format (ADF) Data Description Semantic Graph Model Descriptive metadata about Method, instrument, sample, process, result, etc. Provenance, audit trail Data Cube, Data Package Data Cubes Universal Data Container Chromatogram 2D HDF Analytical data represented by one- or multidimensional arrays of homogeneous data structures. Data Package Virtual File System HDF5 Platform Independent File Format Analytical data represented by arbitrary formats, incl. native instrument formats, images, pdf, video, etc. Specifically designed to store and organize large amounts of scientific data. Slide 4

5 Standardized Data & Metadata Released Dec 2017 Released July 2017 A standardised semantic model for data & metadata. Ontologies Allotrope Data Format Data Description Semantic Model API ADF Explorer Data Models Data Cubes Universal Data Container A set of constraints on the semantic model using data shapes. Data Package Virtual file system ADF Explorer allows browsing of existing ADF files. Coming in 2018 A high-performance binary data format. Instrument, vendor, platform agnostic. An API to allow consistent creation & reading of ADF files. Slide 5

6 Semantics: Reference Ontologies, Constraints and Instance Data Allotrope Data Format (ADF) Instance Data Information about particular experiments Metadata for data cubes and data package is classified by Allotrope Data Models (ADM) Constraints Standards based implementation with W3C SHACL Specify usage of ontologies for experiment data Allotrope Foundation Ontologies (AFO) Classes & Properties Standards based: RDF, OWL, SKOS Aligned with Basic Formal Ontology Modularization: ontology with taxonomy-backbones Reuse of standards: QUDT, ChEBI, Data Cube Ontology etc. is structured by provide standardized vocabulary Slide 6

7 AFO: A Modularized Ontology based on Taxonomy Backbones Top-Level Ontology bfo:continuant bfo:entity bfo:occurrent bfo:specifically dependent bfo:realizable entity bfo:generically dependent bfo:independent bfo:process bfo:disposition Binding bfo:quality bfo:role bfo:function iao:information content entity bfo:material entity obi:planned process Quality Role & Function Result Material Equipment Process Slide 7 has data output

8 AFO: A Modularized Ontology based on Taxonomy Backbones Top-Level Ontology bfo:continuant bfo:entity bfo:occurrent bfo:specifically dependent bfo:realizable entity bfo:generically dependent bfo:independent bfo:process bfo:disposition Binding bfo:quality bfo:role bfo:function iao:information content entity bfo:material entity obi:planned process sample role has role powder has material input weighing mass balance trending plot Quality Role & Function Result Material Equipment Process Slide 8

9 Ontology for HPLC Example material process device result Slide 9

10 Benefits of Reusing Allotrope Data Format Highly reusable, generic data container Flexibility to integrate any custom taxonomy or ontology Can be reused for specification of other standards Improves searchability & findability Supports interoperability & reusability: Makes data understandable Removes ambiguities Simplifies reproducibility Significantly improves information exchange within a community Ready for productive use E.g., data integrity, traceability, audit-trail out-of-the-box Prepares data for Big Data, Data Science, AI applications Allotrope Data Format Data Description Semantic Model Data Cubes Universal Data Container Data Package Virtual file system Slide 10

11 Connecting data, people and organizations

12 Slide 12 Materials Module (Taxonomy Part)

13 Semantic Spectrum of Knowledge Organization Systems Sources Slide 13 Deborah L. McGuinness. "Ontologies Come of Age". In Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, Michael Uschold and Michael Gruninger Ontologies and semantics for seamless connectivity SIGMOD Rec. 33, 4 (December 2004), DOI= Leo Obrst The Ontology Spectrum. Book section in of Roberto Poli, Michael Healy, Achilles Kameas Theory and Applications of Ontology: Computer Applications. Springer Netherlands, 17 Sep Leo Obrst and Mills Davis "Semantic Wave 2008 Report: Industry Roadmap to Web 3.0 & Multibillion Dollar Market Opportunities