Monika Solanki

Considerations regarding Ontology Design Patterns

The Worskhop on Ontology and Semantic Web Patterns (WOP2015, 6th edition) was held on October 11, 2015 in conjunction with the 14th International Semantic Web Conference in Bethlehem, PA, USA. At the workshop, the organizers conducted a discussion with the participants regarding the promises and obstacles of ontology design patterns (ODPs for short). This editorial reports on those discussions. We begin with a brief introduction of ODPs for the unfamiliar reader.

EPCIS Event-Based Traceability in Pharmaceutical Supply Chains via Automated Generation of Linked Pedigrees

In this paper we show how event processing over semantically annotated streams of events can be exploited, for implementing tracing and tracking of products in supply chains through the automated generation of linked pedigrees. In our abstraction, events are encoded as spatially and temporally oriented named graphs, while linked pedigrees as RDF datasets are their specific compositions. We propose an algorithm that operates over streams of RDF annotated EPCIS events to generate linked pedigrees. We exemplify our approach using the pharmaceuticals supply chain and show how counterfeit detection is an implicit part of our pedigree generation. Our evaluation results show that for fast moving supply chains, smaller window sizes on event streams provide significantly higher efficiency in the generation of pedigrees as well as enable early counterfeit detection.

Modelling and linking transformations in EPCIS governing supply chain business processes

Supply chains comprise of complex processes spanning across multiple trading partners. The various operations involved generate large number of events that need to be integrated in order to enable internal and external traceability. Further, provenance of artifacts and agents involved in the supply chain operations is now a key traceability requirement. In this paper we propose a Semantic web/Linked data powered framework for the event based representation and analysis of supply chain activities governed by the EPCIS specification. We specifically show how a new EPCIS event type called Transformation Event can be semantically annotated using EEM - The EPCIS Event Model to generate linked data, that can be exploited for internal event based traceability in supply chains involving transformation of products. For integrating provenance with traceability, we propose a mapping from EEM to PROV-O. We exemplify our approach on an abstraction of the production processes that are part of the wine supply chain.

Collected Research Questions Concerning Ontology Design Patterns

This chapter lists and discusses open challenges for the ODP community in the coming years, both in terms of research questions that will need be answered, and in terms of tooling and infrastructur ...

OntoPedigree: Modelling pedigrees for traceability in supply chains

The sharing of product and process information plays a central role in coordinating supply chains operations and is a key driver for their success. Linked pedigrees - linked datasets, that encapsulate event based traceability information of artifacts as they move along the supply chain, provide a scalable mechanism to record and facilitate the sharing of track and trace knowledge among supply chain partners. In this paper we present OntoPedigree a content ontology design pattern for the representation of linked pedigrees, that can be specialised and extended to define domain specific traceability ontologies. Events captured within the pedigrees are specified using EPCIS - a GS1 standard for the specification of traceability information within and across enterprises, while certification information is described using PROV - a vocabulary for modelling provenance of resources. We exemplify the utility of OntoPedigree in linked pedigrees generated for supply chains within the perishable goods and pharmaceuticals sectors.

A knowledge driven approach towards the validation of externally acquired traceability datasets in supply chain business processes

The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.

Language independent sentiment analysis of the Shukran social network using apache spark

The aim of the Mighty Storage Challenge (MOCHA) at ESWC 2017 was to test the performance of solutions for SPARQL processing in aspects that are relevant for modern applications. These include ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The challenge tested the systems against data derived from real applications and with realistic loads. An emphasis was put on dealing with data in form of streams or updates.

Enhancing Visibility in EPCIS Governing Agri-Food Supply Chains via Linked Pedigrees

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services EPCIS is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code EPC. In this paper, the authors propose a framework that utilises events and EPCs in the generation of linked pedigrees-linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.

Detecting EPCIS exceptions in linked traceability streams across supply chain business processes

The EPCIS specification provides an event oriented mechanism to record product movement information across stakeholders in supply chain business processes. Besides enabling the sharing of event-based traceability datasets, track and trace implementations must also be equipped with the capabilities to validate integrity constraints and detect runtime exceptions without compromising the time-to-deliver schedule of the shipping and receiving parties. In this paper we present a methodology for detecting exceptions arising during the processing of EPCIS event datasets. We propose an extension to the EEM ontology for modelling EPCIS exceptions and show how runtime exceptions can be detected and reported. We exemplify and evaluate our approach on an abstraction of pharmaceutical supply chains.