semantic blockchains in the supply chain
TRANSCRIPT
Semantic blockchains in the supply chain
Christopher Brewster Aston University
Outline• Information integration in the agrifood supply chain
• Semantic web technologies
• Semantic Web technologies in the Food System: Linked Pedigrees
• Some limitations
• Blockchain technologies
• Integrating Semantics and the Blockchain - some initial thoughts
The Problem
The Food Supply Chain• From Farm to Fork
• The agri-food system includes much more
• More and more parts of this supply chain and agri-food system are leaving digital trace … in James Scott’s terms becoming more “legible”.
Data - Information - Knowledge
• The food supply chain involves hundred of actors, thousands of processes, millions of products and (potentially) billions of data points!
• Children believe milk comes from supermarkets!
• Too much or too little data?
• Why do we need it?
Characteristics of Supply Chain
• Large numbers of participants
• Heterogeneity of participants
• Huge variety in ICT uptake
• Poor information flow (need to know attitude)
• Only one up, one down data flow
• Solved by regulation and certification
Food supply chain is …• A highly heterogenous loosely coupled large-scale
network of entities with variable but largely minimal degrees of communication and trust between the actors
Drivers for Data Integration
• Need for transparency - tracking and tracing
• Desire for food awareness - on the part of consumers, but not only
• Regulatory pressure - e.g.EU Regulation 1169/2011
• New business opportunities ….
Food Crises and Scandals
• Major driver for greater data integration (whether open or closed).
• E. Coli in Germany in 2011 - spanish growers lost over €200M
• Horsemeat scandal across Europe in 2013 - impact very great on some supermarkets
Lack of Data Integration• Both scandals suffered from lack of data and data
integration
• E. Coli - who affected? what purchased? where? when? and who participated in the supply chain
• Horsemeat - six months for Irish FSA to map the supply chain network
• Need for greater supply chain transparency = need for data integration
Tracking, tracing and Visibility
• Core demand is to make tracking and tracing easy, AKA supply chain “visibility”
• “Visibility is the ability to know exactly where things are at any point in time, or where they have been, and why” — GS1
• Major challenge
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Trust - 1
Trust - 2
• More information, more data = more trust
What role semantic technologies?
Key Features of Semantic Technologies
• Unique identifiers (URIs) — enables consistency and data accretion
• Common vocabularies/ontologies/data schemata — creates a tendency towards standardisation WITHOUT losing flexibility
• Linking and mappings - create a natural space for new knowledge and data integration
• Logical rigour — rules for validation and quality control can be written
AKTive Food (2005)• A bit of history
• Paper on “Semantic Web based knowledge conduits for the Organic Food Industry”
• Centred on decision support for a restaurant based on data crawled from semantic web marked up websites of food producers
• Nice vision …. but no implementation
Linked Pedigrees• Based on “pedigree” concept common in
pharmaceutical industry - an audit trail which record path of ownership
• Based on GS1 standards (pedigree standard + EPCIS)
• “Linked pedigrees” use semantic web/linked data principles
• Involves formalisation of EPCIS standard in two ontologies
Linked Pedigrees• Datasets described and accessed using linked data principles.
• Encapsulate the knowledge required to trace and track products in supply chains on a Web scale.
• Facilitate the interlinking of a variety of related and relevant data, i.e., GS1 product master data with event data PLUS other data outside the GS1 system.
• Based on a domain independent data model for the sharing of knowledge among Semantic Web/Linked data aware systems deployed for the tracking, tracing and data capture.
• Product knowledge shared among partners as products physically flow downstream or upstream in the supply chain.
Linked Pedigree Architecture
Linked Pedigrees and EPCIS• Formalisations of:
• EEM - The EPCIS Event Model
• CBV - Core Business Vocabulary
• This allows the representation of EPCIS events on the Web of Data
• This enables sharing and traceability of information
• Tracking of inconsistencies
Socio-technical Limitations• Heterogeneity of the food system - so many
different actors, in size and shape
• Continuous changes - actors entering and leaving the market
• Lack of trust - actors (farmers, food producers) do not trust overarching systems
• Cost - margins in the food system are very tight
Key Problems• Any form of centralised
data runs into data control issues. Who know what? (cf. Uber as an example)
• If each actor must keep their triple store up and running - data access issues (important in food crises)
What role blockchain technologies?
What is the blockchain?• A file called The Blockchain is spread over
millions of machines
• Which use proof of work and byzantine consensus
• To provide a set of chained hashes and digital signatures
• To create an unforgeable record of …. (e.g.) who owns how much bitcoin
Blockchain - another definition
• “A blockchain is a magic computer that anyone can upload programs to and leave the programs to self-execute, where the current and all previous states of every program are always publicly visible, and which carries a very strong cryptoeconomically secured guarantee that programs running on the chain will continue to execute in exactly the way that the blockchain protocol specifies.” — Vitalik Buterin (founder of Ethereum)
Blockchain• Developed originally as part of Bitcoin
• Provides underlying distributed ledger for Bitcoin
• HOWEVER, quite separate from Bitcoin and has potentially many other uses
• Lots of eager uptake with many startups being founded around this technology (Ethereum, Bitshares, Helloblock, Ripple Labs etc.)
Blockchain in the supply chain
• Not my idea! Other people have thought of this!
• Startup provenance.org wants to use the blockchain to “tell a story” about a product from producer to end consumer. Currently focussing on certification data!
• Still working on on what data to represent ….
Semantic Blockchains• Concept: Construct an architecture where some or all of
the data involved in Linked Pedigree is held on the block chain
• Result:
• Distributed database would resolve some trust issues
• Guarantee of continuous uptime (so if an actor disappears, their data is still accessible)
• Rules can be written as to who has access to data using specific governance algorithms
Step 1: Basic Usage
Eliminate the problems of data
centralisation
Step 2: More advanced Usage
Guarantee accessibility of data
now and in future
Other potential Consequences
• Disintermediation of GS1 for product data
• Product data, tracking and tracing and supply chain visibility at very low cost. This could be very important for small scale producers/developing country producers
• Standardising supply chain data schemata/ontologies by the back door
Conclusions• We have argued for the importance of data
integration in the agrifood supply chain
• We showed the applicability of semantic technologies in the supply chain and introduced the concept of “linked pedigrees”.
• We then suggest that blockchain technologies could further improve this technology stack and solve some problems e.g.lack of trust in centralised data control
Thanks
• Monika Solanki for all the technical work on Linked Pedigrees, EEM, CBV and much else
• Vinay Gupta for conversations leading to the Semantic Blockchain ideas
• Jessie Baker for explaining provenance.org
References• Christopher Brewster, Hugh Glaser, and Barny Haughton. “AKTive Food: Semantic Web based knowledge conduits for the
Organic Food Industry.” In Proceedings of the ISWC Worskshop Semantic Web Case Studies and Best Practice for eBusiness (SWCASE 05) , 4th International Semantic Web Conference, 7 November (Galway, Ireland, 2005). URL http://www.cbrewster.com/papers/Brewster_SWCASE.pdf
• Monika Solanki and Christopher Brewster. “OntoPedigree: A content ontology design pattern for traceability knowledge representation in supply chains.” Semantic Web – Interoperability, Usability, Applicability (2015). URL http://goo.gl/OdUPg0
• Monika Solanki and Christopher Brewster. “Enhancing visibility in EPCIS governing Agri-food Supply Chains via Linked Pedigrees.” International Journal on Se- mantic Web and Information Systems 10 (2014). (Impact Factor 0.393), URL http://www.ijswis.org/?q=node/52
• Monika Solanki and Christopher Brewster. “Consuming Linked data in Supply Chains: Enabling data visibility via Linked Pedigrees.” In Proceedings of the Fourth Inter- national Workshop on Consuming Linked Data (COLD2013), held at the Interna- tional Semantic Web Conference (ISWC 2013), 21-25 October 2013 (2013). URL http://www.cbrewster.com/papers/Solanki_COLD13.pdf
• Monika Solanki and Christopher Brewster. “Representing Supply Chain Events on the Web of Data.” In Proceedings of the 3rd International Workshop on Detection, Represen- tation, and Exploitation of Events in the Semantic Web (DeRiVE 2013), , held at the International Semantic Web Conference (ISWC 2013), 21-25 October 2013 (2013). URL http://www.cbrewster.com/papers/Solanki_DeRiVE13.pdf
• Monika Solanki and Christopher Brewster. “EPCIS event based traceability in pharmaceu- tical supply chains via automated generation of linked pedigrees.” In International Semantic Web Conference 2014 (ISWC 2014) (Rivo di Garda, 2014). (ISWC accep- tance rate: 21.1% 180 full submissions, 29 accepted, 9 conditionally accepted), URL http://www.cbrewster.com/papers/Solanki_ISWC14.pdf