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Diathesis alternation describes the property of language that individual verbs can be used in different subcategorization frames. However, seemingly similar verbs such as drizzle and spray can behave differently in terms of the alternations they can participate in (drizzle/spray water on the plant; *drizzle/spray the plant with water). By hypothesis, primary linguistic data is not sufficient to learn which verbs alternate and which do not. We tested two state-of-the-art machine learning models trained by self supervision, and found little evidence that they could learn the correct pattern of acceptability judgement in the locative alternation. This is consistent with a poverty of stimulus argument that primary linguistic data does not provide sufficient information to learn aspects of linguistic knowledge. The finding has important consequences for machine learning models trained by self supervision, since they depend on the evidence present in the raw training input.

To ensure safe and efficient operations, all offshore operations follow a plan devised to take into account current operation conditions and identify the optimum workflow with the minimum risk potential. Previously, planners had to manually consult eight data sources, each with a separate UI, and summarise the plan in a.pdf document. Equinor's Operation Planning Tool (OPT) has been developed to easily present the planners with the technical conditions of a platform, identify potentially dangerous combinations of concurrent activities, and propose learnings from eight years’ worth of incident recordings – all relevant to the current list of planned activities. The tool aims to answer questions such as ‘are other activities planned for the same time which would make this activity unsafe?’ or ‘have incidents previously occurred whilst performing similar tasks on this equipment type?’. This paper details the development of the OPT with a particular focus on the application of Natural Language Understanding for extracting equipment types and tasks involved in previous incidents and relating these to planned activities. Utilising natural language processing techniques, a system has been developed that mines the content of Equinor's incident database, and assigns context to incidents, by identifying the systems, activities and equipment involved and the conditions on the asset at the time of the incident. The same context is also discovered from the content of planned activities. These key concepts are organised into a knowledge graph synthesising Equinor's institutional safety and operational experience. The OPT has reduced time spent planning by providing a single interface detailing a plant's technical conditions, all planned work orders and relevant lessons learned from previous incidents. By reducing the reliance on personal experience, the tool has provided subjectively improved risk identification and handling, plus faster knowledge transfer to new employees as well as focussed cross-platform knowledge sharing. The success of the tool highlights the strength of combining data and leveraging the vast quantities of historic data available both in unstructured and structured forms to create a safe, offshore work environment.

PurposeBy providing interoperability users can be supported in sharing and reusing vocabularies and knowledge. Ontology alignment plays an important role in the context of semantic interoperability. Usually ontology alignment tools generate results that are difficult to understand or assess. In order to enable users to check and improve alignment results and to understand their consequences information visualization techniques are used. The purpose of this paper is to discuss the relevant quality aspects in ontology alignment as well as current activities and available tools.Design/methodology/approachBased on a literature study quality measures for ontology alignment identified and requirements for visual ontology alignment are defined. As a proof of concepts a prototype called AlViz was developed.FindingsInformation visualization offers appropriate methods for the assessment of ontology alignment results. Different levels of detail and overview help users to navigate and understand the alignments. The assessment of semi‐structured resources by users involves learning activities. The neighborhood of the entity under investigation bears relevant semantic information. Therefore, assessment may include crisscrossing acquisition of knowledge representations and their semantics.Originality/valueAlong a comprehensive framework alignment assessment tasks are identified and visualization tool is introduced and applied which aims at making ontology alignment results manageable and comprehensible.

B-SCP (Business Strategy, Context, and Process) is a promising framework addressing alignment of IT with business strategy from a requirements engineering perspective. The B-SCP approach combines goal and context modeling, and business processes, into a generic modeling framework that deconstructs these to IT requirements and context. However, a problem with the B-SCP framework is that it is difficult to track dependencies between requirements in a project of realistic complexity. To address this we discuss how the RDF (Resource Description Framework) data model with OWL (Web Ontology Language) semantics will greatly benefit an implementation using B-SCP. Our contribution is to extend B-SCP by describing an ontology data structure for representing the requirements and the complex rules which map them together. The benefit in our approach is that it provides a comprehensive way to validate the decomposition of the requirements. Seven–Eleven Japan is used as an exemplar to demonstrate improved productivity and consistency of B-SCP.

The Environment Web (EW) is the official database for emissions and discharges from the offshore oil and gas industry in Norway. Currently we are working on a project to describe and align terms in the EW application according to the ISO 15926 Reference Data Library (RDL). One of our goals is to ensure that the EW terms in the RDL can be used as a reference point for all systems using EW terms. Therefore the definitions of the EW constructs in the RDL need to be unambiguous. Moreover, another goal is to enrich the ISO 15926 ontology by adding terms from the EW domain.We briefly describe our experiences and challenges faced so far when mapping terms from the EW database to the ISO15926 Ontology.

B-SCP is a promising framework addressing alignment of IT with business strategy from a requirements engineering persective. A problem with the B-SCP framework is that it is extremely difficult to track dependencies between requirements in a project of realistic complexity. We discuss how the RDF data model with OWL semantics, will greatly benefit an implementation using B-SCP. Our contribution is to extend B-SCP by describing an ontology data structure for representing the requirements and the complex rules which map them together. Seven Eleven-Japan is used as an exemplar to demonstrate improved productivity and consistency of B-SCP.

With a literature study we found an enormous number of ontology visualization tools. Many of them apply graph visualization but there are other approaches as well. We have identified interesting solutions for dealing with the complexity of large ontologies. Ontology engineering, ontology mapping and alignment can benefit from Information Visualization. Our collection is a starting point to demonstrate the usefulness of Information Visualization techniques, however, a detailed evaluation would be the next step to consolidate this research area and help to boost the adoption of ontologies in common Web applications.

Semantic Web applications often rely on the reuse of underlying data from legacy information systems. The motivation for our research is how to make this data accessible for use in such applications. We propose the use of ontologies and conceptual modelling in an overall approach for data interoperability. The approach incorporates a process for ontology alignment using our tool for visual ontology alignment. First results from our tool evaluation were promising and show that visualization is useful for locating additional candidate alignments by an end user.

We develop a multiple-view tool called AlViz, which aims at supporting the ontology alignment process visually. Combing views on several levels of abstraction, the tool tries to make the 'relatedness' between entities accessible. Based on a literature study we identified relevant phases emerging in ontology alignment. We extended a general alignment framework in order to reflect the adoption of visualization techniques. This framework builds the background for our user study. We evaluate visual ontology alignment with AlViz in three stages: (1) Participative software development, (2) usability evaluation, and (3) utility study. The evaluation methods proved viable even though our study design is challenging.

We introduce a multiple-view tool called AlViz, which supports the alignment of ontologies visually. Ontologies play an important role for interoperability between organizations and for the semantic Web because they aim at capturing domain knowledge in a generic way and provide a consensual understanding of a domain. Alignment is the process where for each entity in first ontology we try to find a corresponding entity in the second ontology with the same or the closest meaning. Existing ontology alignment tools do not adequately provide a way for users to analyze the results. While many alignment tools generate lists of mappings it is difficult to analyze these alignments without examining every pairwise correspondence in the output files and even then it is an overwhelming task. We propose the use of visualization techniques to facilitate user understanding of the ontology alignment results. AlViz is implemented as a tab plug-in for Protege

Ontologies play an important role for the semantic web because they aim at capturing domain knowledge in a generic way and provide a consensual understanding of a domain. Due to the number of ontologies available the need for mapping or bringing them into alignment has prompted a surge of tools and algorithms to be developed for this purpose. We describe some of these ontology alignment tools and discuss issues and shortcomings in current state of the art. From this analysis we propose the use of visualization techniques to facilitate understanding of the ontology alignment results. Finally we briefly describe AlViz, our visual ontology alignment tool.

Explores the importance of semantic integrity during data warehouse design and its impact on the successful use of the implemented warehouse. This was achieved through a detailed case study. Consequently, a conceptual framework for describing inter-subjective meaning in data modelling has been developed. The purpose of the framework is to provide a theoretical basis for explaining how a data model is interpreted through the meaning levels of understanding, connotation and generation, and also how a data model is created from an existing meaning structure by intention, generation and action. This paper also describes inhibiting factors for understanding the physical data model based on the case study findings. Furthermore strategies are suggested to address the factors inhibiting the generation of meaning from a data model, in particular for improving understanding. The result of the exploration is the recognition that the implementation of a data warehouse may not assist with providing a detailed understanding of the semantic content of the data warehouse.