International Journal of Metadata, Semantics and Ontologies
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International Journal of Metadata, Semantics and Ontologies (6 papers in press)
Formalizing Contextual Expert Knowledge for Causal Discovery in linked Knowledge Graphs about Transformation Processes: Application to processing of bio-composites for food packaging by Melanie Munch, Patrice Buche, Cristina Manfredotti, Pierre-Henri Wuillemin, Helene Angellier-Coussy Abstract: With numerous parameters and criteria to take into account, transformation\r\nprocesses are a challenge to model and reason about. This work can be eased thanks to knowledge graphs, which are a widespread practice for formalizing knowledge associated with structured and specialized vocabulary about a given domain. They allow to draw semantic relations between concepts, and thus offer numerous tools for reasoning over complex queries. Yet, some of these queries in transformation processes might rely on an additional layer hard to transcribe: uncertainty. In this article, we present how knowledge graphs and probabilistic models can benefit each other for reasoning over transformation processes and address the necessity of formalizing contextual expert knowledge for this\r\ncombination. We then show how this can be used for (1) reverse engineering approaches\r\nand (2) linking knowledge bases, through a detailed example on the process of biocomposites for food packaging. Keywords: Knowledge graph; Probabilistic model; Expert knowledge; Causality; Linked\r\nOpen Data.
Automated subject indexing using word embeddings and controlled vocabularies: a comparative study by Michalis Sfakakis, Leonidas Papachristopoulos, Kyriaki Zoutsou, Christos Papatheodorou, Giannis Tsakonas Abstract: Text mining methods contribute significantly to the understanding and the management of digital content, increasing the potential of entry links. This paper introduces a method for subject analysis combining topic modelling and automated labelling of the generated topics exploiting terms from existing knowledge organisation systems. A testbed was developed in which the Latent Dirichlet Allocation (LDA) algorithm was deployed for modelling the topics of a corpus of papers related to the Digital Library Evaluation domain. The generated topics were represented in the form of bags-of-words word embeddings and were utilised for retrieving terms from the EuroVoc Thesaurus and the Computer Science Ontology (CSO). The results of this study show that the domain of DL can be described with different vocabularies, but during the process of automatic labelling the context needs to be taken into account. Keywords: subject indexing; similarity measures; text classification; machine learning; word embedding. DOI: 10.1504/IJMSO.2021.10050922
EPIC: an iterative model for metadata improvement by Hannah Tarver, Mark Edward Phillips, Ana Krahmer Abstract: This paper provides a case study of iterative metadata correction and enhancement at the University of North Texas (UNT), within a model that we have developed to describe this process: Evaluate, Prioritise, Identify, Correct (EPIC). These steps are illustrated within the paper to show how they function at UNT and why it may serve as a useful tool for other organisations. We suggest that the EPIC model works for ongoing assessment, but is particularly useful for large remediation and enhancement projects to plan timelines and to allocate the people and resources needed to determine what issues should be addressed (evaluate), to rate their level of severity, importance, or difficulty (prioritise), to define subsets or records that are affected (identify) and to make changes based on prioritisation (correct). Keywords: metadata quality; iterative processes; enhancement projects; models. DOI: 10.1504/IJMSO.2021.10050924
What process can a university follow for open data? The University of Crete case by Yannis Tzitzikas, Marios Pitikakis, Giorgos Giakoumis, Kalliopi Varouha, Eleni Karkanaki Abstract: All public bodies in Greece, including universities, are obliged to comply with the national legal framework and policy on open data. An emerging concern is how such a big and diverse organisation could develop supporting procedures from an administrative, legal and technical standpoint, that will enhance and expand the level of the provided open data related services. In this paper, we describe our experience, at the University of Crete, for tackling these requirements. In particular, (a) we detail the steps of the process that we followed, (b) we show how an Open Data Catalogue can be exploited also in the first steps of this process, (c) we describe the platform that we selected, how we organised the catalogue and the metadata selection, (d) we describe extensions that were required, (e) we motivate and describe various additional services that we developed and (f) we discuss the current status and possible next steps. Keywords: open data; university open data; data sharing. DOI: 10.1504/IJMSO.2021.10050925
An ontology proposal for a corpus of letters of Vincenzo Bellini: formal properties of physical structure and the case of rotated texts by Salvatore Cristofaro, Pietro Sichera, Daria Spampinato Abstract: In this paper the formal OntoBelliniLetters ontology is described concerning the corpus of Vincenzo Bellini's letters kept at the Belliniano Civic Museum of Catania. This ontology is part of a wider project - the BellinInRete project - one of whose aims is the development of a more general and complete ontology for the whole of Vincenzo Bellini's legacy preserved in the museum. The main concepts and relations building up the ontology knowledge base are described and discussed and some formal properties of them are presented. The ontology schema is inspired by the CIDOC Conceptual Reference Model (CIDOC CRM). Keywords: letters; ontology; Vincenzo Bellini; CIDOC CRM; text arrangement. DOI: 10.1504/IJMSO.2021.10050926
Making heterogeneous smart home data interoperable with the SAREF ontology by Roderick Van Der Weerdt, Victor De Boer, Laura Daniele, Barry Nouwt, Ronald Siebes Abstract: SAREF is an ontology created to enable interoperability between smart devices, but there is a lack in the literature of practical examples to implement SAREF in real applications. We validate the practical implementation of SAREF through two approaches. We first examine two methods to map the IoT data available in a smart home into linked data using SAREF: (1) by creating a template-based mapping to describe how SAREF can be used and (2) by using a mapping language to demonstrate it can be simple to map, while still using SAREF. The second approach demonstrates the communication capabilities of IoT devices when they share knowledge represented using SAREF and describes how SAREF enables interoperability between different devices. The two approaches demonstrate that all the information from various data sets of smart devices can successfully be transformed into the SAREF ontology and how SAREF can be applied in a concrete interoperability framework. Keywords: IoT; SAREF; ontology; data mapping; smart home. DOI: 10.1504/IJMSO.2021.10050927