Adam Shepherd

The GeoLink Modular Oceanography Ontology

GeoLink is one of the building block projects within EarthCube, a major effort of the National Science Foundation to establish a next-generation knowledge infrastructure for geosciences. As part of this effort, GeoLink aims to improve data retrieval, reuse, and integration of seven geoscience data repositories through the use of ontologies. In this paper, we report on the GeoLink modular ontology, which consists of an interlinked collection of ontology design patterns engineered as the result of a collaborative modeling effort. We explain our design choices, present selected modeling details, and discuss how data integration can be achieved using the patterns while respecting the existing heterogeneity within the participating repositories.

The OceanLink project

Todays scientific investigations are producing large numbers of scholarly products. These products continue to increase in diversity and complexity as researchers recognize that scholarly achievements are not only published articles but also datasets, software, and associated supporting materials. OceanLink is an online platform that addresses scholarly discovery and collaboration in the ocean sciences. The OceanLink project leverages Semantic Web technologies, web mining, and crowdsourcing to identify links between data centers, digital repositories, and professional societies to enhance discovery, enable collaboration, and begin to assess research contribution.

Where big data meets linked data: Applying standard data models to environmental data streams

In August 2015, a new seafloor observatory was deployed in Galway Bay, Ireland. The sensors on the observatory platform are connected by fibre-optic cable to a shore station, where a broadband connection allows data transfer to the Marine Institutes data centre. This setup involved the development of a new data acquisition system which takes advantage of open source streaming data solutions developed in response to the Big Data paradigm, in particular the Velocity aspect. This activity merges concepts from the arenas of both Big Data and Internet of Things where data standardisation is not normally considered. This paper considers the architecture implemented to stream marine data from instrument to end user and offers suggestions on how to standardise these data streams.

The GeoLink knowledge graph

ABSTRACT GeoLink has leveraged linked data principles to create a dataset that allows users to seamlessly query and reason over some of the most prominent geoscience metadata repositories in the United States. The GeoLink dataset includes such diverse information as port calls made by oceanographic cruises, physical sample metadata, research project funding and staffing, and authorship of technical reports. The data has been published according to best practices for linked data and is publicly available via a SPARQL Protocol and RDF Query Language (SPARQL) end point that at present contains more than 45 million Resource Description Framework (RDF) triples together with a collection of ontologies and geo-visualization tools. This article describes the geoscience datasets, the modeling and publication process, and current uses of the dataset. The focus is on providing enough detail to enable researchers, application developers and others who wish to leverage the GeoLink data in their own work to do so. The dataset is available at http://hdl.handle.net/1912/9524.

Semantics all the way down: the Semantic Web and open science in big earth data

Abstract Semantic technologies have emerged as a prominent research area within Big Earth Data. These technologies have provided significant benefits for data discovery and integration. Yet, the formality of the Semantic Web, in languages such as the Web Ontology Language (OWL), does not always integrate well with the numerical, statistical, and geometric methods of the geosciences. Two prominent challenges in this area are how to semantically model individual measurements and what to do when geoscience needs are not addressed by languages such as OWL. This has led to a fragmented Big Earth Data community with either no solution or incompatible semantic solutions. We use an oceanographic example to highlight the limitations and challenges surrounding the semantic encoding of observations and the use of semantics during analysis. We then present potential solutions to each challenge showing that a full end-to-end application of semantic technologies is not only feasible, but beneficial to Big Earth Data.

Experiences of a “semantics smackdown”

Within the field of ocean science there is a long history of using controlled vocabularies and other Semantic Web techniques to provide a common and easily exchanged description of datasets. As an activity within the European Union, United States, Australian-funded project “Ocean Data Interoperability Platform”, a workshop took place in June 2014 at Rensselaer Polytechnic Institute to further the use of these Semantic Web techniques with the aim of producing a set Linked Data publication patterns which describe many parts of a marine science dataset. During the workshop, a Semantic Web development methodology was followed which promoted the use of a team with mixed skills (computer, data and marine science experts) to rapidly prototype a model ontology which could be iterated in the future. In this paper we outline the methodology employed in the workshop, and examine both the technical and sociological outcomes of a workshop of this kind.