The joint W3C (World Wide Web Consortium) and OGC (Open Geospatial Consortium) Spatial Data on the Web (SDW) Working Group developed a set of ontologies to describe sensors, actuators, samplers as ...well as their observations, actuation, and sampling activities. The ontologies have been published both as a W3C recommendation and as an OGC implementation standard. The set includes a lightweight core module called SOSA (Sensor, Observation, Sampler, and Actuator) available at: http://www.w3.org/ns/sosa/, and a more expressive extension module called SSN (Semantic Sensor Network) available at: http://www.w3.org/ns/ssn/. Together they describe systems of sensors and actuators, observations, the used procedures, the subjects and their properties being observed or acted upon, samples and the process of sampling, and so forth. The set of ontologies adopts a modular architecture with SOSA as a self-contained core that is extended by SSN and other modules to add expressivity and breadth. The SOSA/SSN ontologies are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Internet of Things. In this paper we give an overview of the ontologies and discuss the rationale behind key design decisions, reporting on the differences between the new SSN ontology presented here and its predecessor Web Semantics: Science, Services and Agents on the World Wide Web 17 (2012), 25–32 developed by the W3C Semantic Sensor Network Incubator group (the SSN-XG). We present usage examples and describe alignment modules that foster interoperability with other ontologies.
Abstract The exponential growth of textual data in the digital era underlines the pivotal role of Knowledge Graphs (KGs) in effectively storing, managing, and utilizing this vast reservoir of ...information. Despite the copious amounts of text available on the web, a significant portion remains unstructured, presenting a substantial barrier to the automatic construction and enrichment of KGs. To address this issue, we introduce an enhanced Doc‐KG model, a sophisticated approach designed to transform unstructured documents into structured knowledge by generating local KGs and mapping these to a target KG, such as Wikidata. Our model innovatively leverages syntactic information to extract entities and predicates efficiently, integrating them into triples with improved accuracy. Furthermore, the Doc‐KG model's performance surpasses existing methodologies by utilizing advanced algorithms for both the extraction of triples and their subsequent identification within Wikidata, employing Wikidata's Unified Resource Identifiers for precise mapping. This dual capability not only facilitates the construction of KGs directly from unstructured texts but also enhances the process of identifying triple mentions within Wikidata, marking a significant advancement in the domain. Our comprehensive evaluation, conducted using the renowned WebNLG benchmark dataset, reveals the Doc‐KG model's superior performance in triple extraction tasks, achieving an unprecedented accuracy rate of 86.64%. In the domain of triple identification, the model demonstrated exceptional efficacy by mapping 61.35% of the local KG to Wikidata, thereby contributing 38.65% of novel information for KG enrichment. A qualitative analysis based on a manually annotated dataset further confirms the model's excellence, outshining baseline methods in extracting high‐fidelity triples. This research embodies a novel contribution to the field of knowledge extraction and management, offering a robust framework for the semantic structuring of unstructured data and paving the way for the next generation of KGs.
Gesture Elicitation Studies (GES) are a widely used empirical method to develop gesture vocabularies, interaction models and methods for gesture-based systems in different contexts. While GES show ...great promise to identify user-defined gestures, there are inherent problems with current methods used for GES. Especially during the ongoing pandemic, it has been nearly impossible to conduct in-person, in-lab GES, while ensuring the safety and well-being of the participants, and complying with social distancing regulations. Further, with prevailing experiment designs, increasing the number of participants is time consuming, while in-lab environments also limit ecological validity. This study explores an intuitive way of conducting self-guided GES using immersive Virtual Reality (VR), utilizing its capability to simulate various contexts to enhance ecological validity. We present a methodology and a tool set that use an immersive VR environment to conduct ecologically valid GES (as a use case) while requiring minimal involvement by the investigator. We evaluate our method using the case of a smart home environment and measure participant acceptance and discuss opportunities and challenges involved in this method. We believe that this study will help HCI research to move forward with participatory design research, even when lab experiments are difficult to conduct.
Where to search top-K biomedical ontologies? Oliveira, Daniela; Butt, Anila Sahar; Haller, Armin ...
Briefings in bioinformatics,
07/2019, Letnik:
20, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Abstract
Motivation
Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent ...concepts in a single or multiple ontologies. Search engines that retrieve ontological resources often suggest an extensive list of search results for a given input term, which leads to the tedious task of selecting the best-fit ontological resource (class or property) for the input term and reduces user confidence in the retrieval engines. A systematic evaluation of these search engines is necessary to understand their strengths and weaknesses in different search requirements.
Result
We have implemented seven comparable Information Retrieval ranking algorithms to search through ontologies and compared them against four search engines for ontologies. Free-text queries have been performed, the outcomes have been judged by experts and the ranking algorithms and search engines have been evaluated against the expert-based ground truth (GT). In addition, we propose a probabilistic GT that is developed automatically to provide deeper insights and confidence to the expert-based GT as well as evaluating a broader range of search queries.
Conclusion
The main outcome of this work is the identification of key search factors for biomedical ontologies together with search requirements and a set of recommendations that will help biomedical experts and ontology engineers to select the best-suited retrieval mechanism in their search scenarios. We expect that this evaluation will allow researchers and practitioners to apply the current search techniques more reliably and that it will help them to select the right solution for their daily work.
Availability
The source code (of seven ranking algorithms), ground truths and experimental results are available at https://github.com/danielapoliveira/bioont-search-benchmark
This article describes the publication of occurrences of Southern Elephant Seals Mirounga leonina (Linnaeus, 1758) as Linked Open Data in two environments (marine and coastal). The data constitutes ...hydrographic measurements of instrumented animals and observation data collected during censuses between 1990 and 2017. The data scheme is based on the previously developed ontology BiGe-Onto and the new version of the Semantic Sensor Network ontology (SSN). We introduce the network of ontologies used to organize the data and the transformation process to publish the dataset. In the use case, we develop an application to access and analyze the dataset. The linked open dataset and the related visualization tool turned data into a resource that can be located by the international community and thus increase the commitment to its sustainability. The data, coming from Península Valdés (UNESCO World Heritage), is available for interdisciplinary studies of management and conservation of marine and coastal protected areas which demand reliable and updated data.
The rapid advancement and ubiquitous penetration of mobile networks and software-defined networking technology enable us to sense, predict and control the physical world using information technology ...– the so-called Internet of Things (IoT).1 Consequently, business models and processes have been redesigned across a broad range of industries where objects are connected over the Web for communication with other objects on the Web, leading to the so-called Web of Things (WoT) on top of the IoT.Pervasive connectivity, smart personal devices, for example in our homes, and demand for data testify to a WoT that will continue to grow. New devices are being developed and are becoming cheaper, making their integration into everyday objects ever more feasible, and as people buy into WoT technology, economies of scale lend themselves to the creation of ever more data-centric businesses.
Knowledge Graphs (KGs) have proliferated on the Web since the introduction of knowledge panels to Google search in 2012. KGs are large data-first graph databases with weak inference rules and ...weakly-constraining data schemes. SHACL, the Shapes Constraint Language, is a W3C recommendation for expressing constraints on graph data as shapes. SHACL shapes serve to validate a KG, to underpin manual KG editing tasks, and to offer insight into KG structure. Often in practice, large KGs have no available shape constraints and so cannot obtain these benefits for ongoing maintenance and extension. We introduce Inverse Open Path (IOP) rules, a predicate logic formalism which presents specific shapes in the form of paths over connected entities that are present in a KG. IOP rules express simple shape patterns that can be augmented with minimum cardinality constraints and also used as a building block for more complex shapes, such as trees and other rule patterns. We define formal quality measures for IOP rules and propose a novel method to learn high-quality rules from KGs. We show how to build high-quality tree shapes from the IOP rules. Our learning method, SHACLearner, is adapted from a state-of-the-art embedding-based open path rule learner (Oprl). We evaluate SHACLearner on some real-world massive KGs, including YAGO2s (4M facts), DBpedia 3.8 (11M facts), and Wikidata (8M facts). The experiments show that our SHACLearner can effectively learn informative and intuitive shapes from massive KGs. The shapes are diverse in structural features such as depth and width, and also in quality measures that indicate confidence and generality.
Linked Open Data promises to provide guiding principles to publish interlinked knowledge graphs on the Web in the form of findable, accessible, interoperable, and reusable datasets. We argue that ...while as such, Linked Data may be viewed as a basis for instantiating the FAIR principles, there are still a number of open issues that cause significant data quality issues even when knowledge graphs are published as Linked Data. First, to define boundaries of single coherent knowledge graphs within Linked Data, a principled notion of what a dataset is, or, respectively, what links within and between datasets are, has been missing. Second, we argue that to enable FAIR knowledge graphs, Linked Data misses standardised findability and accessability mechanism via a single entry link. To address the first issue, we (i) propose a rigorous definition of a naming authority for a Linked Data dataset, (ii) define different link types for data in Linked datasets, (iii) provide an empirical analysis of linkage among the datasets of the Linked Open Data cloud, and (iv) analyse the dereferenceability of those links. We base our analyses and link computations on a scalable mechanism implemented on top of the HDT format, which allows us to analyse quantity and quality of different link types at scale.
This book constitutes the refereed post-proceedings of six international workshops held in conjunction with the Third International Conference on Business Process Management, BPM 2005, in September ...2005. The 41 revised full papers presented were carefully reviewed and selected. Among the issues addressed are fundamental process modeling, Web service choreography and orchestration, business process reference models, and business processes and services.
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