A Lime-Flavored REST API for Alignment Services

A practical alignment service should be flexible enough to handle the varied alignment scenarios that arise in the real world, while minimizing the need for manual configuration. MAPLE, an orchestration framework for ontology alignment, supports this goal by coordinating a few loosely coupled actors, which communicate and cooperate to solve a matching task using explicit metadata about the input ontologies, other available resources and the task itself. The alignment task is thus summarized by a report listing its characteristics and suggesting alignment strategies. The schema of the report is based on several metadata vocabularies, among which the Lime module of the OntoLex-Lemon model is particularly important, summarizing the lexical content of the input ontologies and describing external language resources that may be exploited for performing the alignment. In this paper, we propose a REST API that enables the participation of downstream alignment services in the process orchestrated by MAPLE, helping them self-adapt in order to handle heterogeneous alignment tasks and scenarios. The realization of this alignment orchestration effort has been performed through two main phases: we first described its API as an OpenAPI specification (a la API-first), which we then exploited to generate server stubs and compliant client libraries. Finally, we switched our focus to the integration of existing alignment systems, with one fully integrated system and an additional one being worked on, in the effort to propose the API as a valuable addendum to any system being developed

Automatic Alignment of Multilingual Resources in the Linguistic Linked Open Data Cloud

The creation of Europe’s Digital Single Market requires interoperable multilingual resources in the Linguistic Linked Open Data (LLOD) cloud. The PMKI project aims to create a public multilingual knowledge management infrastructure, able to establish and manage interoperability between multilingual classification systems (like thesauri) and other language resources. In this paper the standards used by PMKI and a methodology for automatic mapping between multilingual resources, based on an information retrieval framework, is presented

AGROVOC: The linked data concept hub for food and agriculture

Newly acquired, aggregated and shared data are essential for innovation in food and agriculture to improve the discoverability of research. Since the early 1980′s, the Food and Agriculture Organization of the United Nations (FAO) has coordinated AGROVOC, a valuable tool for data to be classified homogeneously, facilitating interoperability and reuse. AGROVOC is a multilingual and controlled vocabulary designed to cover concepts and terminology under FAO's areas of interest. It is the largest Linked Open Data set about agriculture available for public use and its highest impact is through facilitating the access and visibility of data across domains and languages. This chapter has the aim of describing the current status of one of the most popular thesaurus in all FAO’s areas of interest, and how it has become the Linked Data Concept Hub for food and agriculture, through new procedures put in plac

39 Hints to Facilitate the Use of Semantics for Data on Agriculture and Nutrition

In this paper, we report on the outputs and adoption of the Agrisemantics Working Group of the Research Data Alliance (RDA), consisting of a set of recommendations to facilitate the adoption of semantic technologies and methods for the purpose of data interoperability in the field of agriculture and nutrition. From 2016 to 2019, the group gathered researchers and practitioners at the crossing point between information technology and agricultural science, to study all aspects in the life cycle of semantic resources: conceptualization, edition, sharing, standardization, services, alignment, long term support. First, the working group realized a landscape study, a study of the uses of semantics in agrifood, then collected use cases for the exploitation of semantics resources-a generic term to encompass vocabularies, terminologies, thesauri, ontologies. The resulting requirements were synthesized into 39 "hints" for users and developers of semantic resources, and providers of semantic resource services. We believe adopting these recommendations will engage agrifood sciences in a necessary transition to leverage data production, sharing and reuse and the adoption of the FAIR data principles. The paper includes examples of adoption of those requirements, and a discussion of their contribution to the field of data science

From AGROVOC OWL Model towards AGROVOC SKOS Model

AGROVOC is a multilingual structured thesaurus for the agricultural domain, which is owned and maintained by an international community of Agricultural Research Information Institutions. AGROVOC is used all over the world by researchers, librarians, information managers and others, for indexing, retrieving, and organizing data in Agricultural Information Systems. It currently includes 579523 terms in 19 different languages

Migrating bibliographic datasets to the Semantic Web: The AGRIS case. Semantic Web.

In this paper we describe the ongoing move of the AGRIS repository toward a decentralized approach based on Linked Open Data (LOD) (Bizer, et al., 2008). This move has progressively required modifications and enhancements to data, models and workflows. The growing demand for freely accessible data has brought a rise in data distributed using LOD, which combines Resource Description Framework (RDF) (McBride, 2004a) and RDF Schema (McBride, 2004b) with vocabularies such as Dublin Core (DC) (Miles, et al., 2009) and Simple Knowledge Organisation System, together with interfaces such as SPARQL query language for RDF (Prud'hommeaux, et al., 2008). While LOD implementations are by now a well-established pattern, the impacts that such approaches have on underlying business processes is less well understood. The openness of the LOD paradigm can expose flaws in information management workflows. Poor metadata, lack of metrics, vague provenance; all can contribute to the inability of an LOD-enabled system to satisfy the demands of the Semantic Web

Linguistically motivated ontology mapping for the Semantic Web

Knowledge Sharing is a crucial issue in the Semantic Web: SW services expose and share knowledge content (expressed through ontologies and related knowledge bases) arising from distinct languages, locales, and personal perspectives; in this scenario, semantic alignment approaches play a pivotal role, providing viable solutions for integrating heterogeneous resources, still maintaining their local independence. We focus here on a 3-step approach to ontology mapping, which is strongly based on the exploitation of (monolingual and multilingual) linguistic resources for content publishing and discovery, and on a human intervention for supervising the process and assessing semantic links between mapped resources. Our methodology is also being supported by the development of dedicated tools for accompanying knowledge engineers and users across the different steps of creating and integrating ontology resources

Proof and Trust in the OpenAGRIS Implementation

The AGRIS repository is a bibliographic database covering almost forty years of agricultural research. Following the conversion of its indexing thesaurus AGROVOC into a concept-based vocabulary, the decision was made to express the entire AGRIS repository in RDF as Linked Open Data. As part of this exercise, a semantic mashup named OpenAGRIS was developed in order to access the records and use them to dynamically display related data from external systems through both SPARQL queries and traditional web services. The overall process raised numerous issues regarding the relative lack of administrative metadata required to compellingly address the top proof and trust layers of the semantic web stack, both within the AGRIS repository and in external data dynamically pulled into OpenAGRIS. The team began by disambiguating the journals in which the articles were published and converting them into RDF but quickly realized this was only the beginning of a series of necessary steps in moving from a closed to an open world paradigm. Further disambiguation of institutions, authors and AGRIS Centres as well as the use of the VoiD vocabulary and of quality indicator models are discussed and evaluated

Thesaurus Maintenance, Alignment and Publication as Linked Data: The AGROVOC Use Case

The AGROVOC multilingual thesaurus maintained by the Food and Agriculture Organization of the United Nations (FAO) is now published as linked data. In order to reach this goal AGROVOC was expressed in Simple Knowledge Organization System (SKOS), and its concepts provided with dereferenceable URIs. AGROVOC is now aligned with ten other multilingual knowledge organization systems related to agriculture, using the SKOS properties exact match and close match. Alignments were automatically produced in Eclipse using a custom-designed tool and then validated by a domain expert. The resulting data is publicly available to both humans and machines using a SPARQL endpoint together with a modified version of Pubby, a lightweight front-end tool for publishing linked data. This paper describes the process that led to the current linked data AGROVOC and discusses current and future applications and directions