Accepted Manuscript Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information Chengbin Wang, Xiaogang Ma, Jianguo Chen PII:
S0098-3004(17)30518-6
DOI:
10.1016/j.cageo.2018.03.004
Reference:
CAGEO 4103
To appear in:
Computers and Geosciences
Received Date: 6 May 2017 Revised Date:
27 February 2018
Accepted Date: 5 March 2018
Please cite this article as: Wang, C., Ma, X., Chen, J., Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information, Computers and Geosciences (2018), doi: 10.1016/j.cageo.2018.03.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Ontology-Driven Data Integration and Visualization for Exploring Regional Geologic Time and Paleontological Information
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Chengbin Wang1, 2, Xiaogang Ma2*, Jianguo Chen1
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Earth Resources, China University of Geosciences, Wuhan 430074, China
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* Corresponding Author E-mail:
[email protected]
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State Key Laboratory of Geological Processes and Mineral Resources & Faculty of
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Department of Computer Science, University of Idaho, Moscow ID 83844, USA
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Abstract: Initiatives of open data promote the online publication and sharing of large
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amounts of geologic data. How to retrieve information and discover knowledge from
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the big data is an ongoing challenge. In this paper, we developed an ontology-driven
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data integration and visualization pilot system for exploring information of regional
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geologic time, paleontology, and fundamental geology. The pilot system
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(http://www2.cs.uidaho.edu/~max/gts/) implemented the following functions:
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modeling and visualization of a geologic time scale ontology of North America,
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interactive retrieval and display of fossil information, geologic map information query
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and comparison with fossil information. A few case studies were carried out in the
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pilot system for querying fossil occurrence records from Plaeobiology Database and
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comparing them with information from the USGS geologic map services. The results
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show that, to improve the compatibility between local and global geologic standards,
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bridge gaps between different data sources, and create smart geoscience data services,
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it is necessary to further extend and improve the existing geoscience ontologies and
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use them to support functions to explore the open data.
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Key Words: Ontology; Local Geologic Time Standard; Paleontology; Geologic Map;
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Open Data
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28 1 Introduction
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In the past decade, the approaches of open data and big data have attracted increasing
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attention, and they are now widely used in different knowledge domains. Many
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governmental agencies and scientific organizations have published data on the
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Internet for others to reuse. In the domain of geosciences, data of various subjects (e.g.
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geologic map, mineral deposit, fossil, geochemistry, minerology and petrology, etc.)
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are already made open and accessible online. Due to their disciplinary background,
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those open geoscience data are usually stored in repositories each with its focused
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subject and are short of inter-connections. There exist both challenges and
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opportunities to make connections among those ‘silo’ data sources, develop
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interactive data services, detect patterns in assembled datasets, and propose new
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topics for knowledge discovery.
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To address challenges caused by the high volume, variety and velocity of big data,
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Sheth (2014a, 2014b) utilized the semantic perception, agreement and continuous
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semantics methods to transform big data into structured smart data, that is, data of
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smaller volume and actionable information. He presented successful case studies in
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personalized and actionable health information. Similar research topics of building
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ACCEPTED MANUSCRIPT smart data and making knowledge discovery also exist in geosciences. The standards
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developed by the World Wide Web Consortium (W3C) and the Open Geospatial
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Consortium (OGC), such as XML (eXtensible Markup Language)1, RDF (Resource
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Description Framework)2, RDFS (RDF Schema)3, SKOS (Simple Knowledge
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Organization System)4, OWL (Web Ontology Language)5, WFS (Web Feature
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Service)6, WMS (Web Map Service)7 and WCS (Web Coverage Service)8, provide
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the fundamental building blocks for adding structures and meanings into online
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datasets. In recent years, the geoscience community has made remarkable progress on
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semantic models, ontologies and open data frameworks (Buccella et al., 2009; Ma and
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Fox, 2013; Sen and Duffy, 2005; Zheng et al., 2015). Several geoscience data
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frameworks, such as OneGeology9, USGIN (U.S. Geoscience Information Network)10,
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AuScope11 and USGS (U.S. Geological Survey) Mineral Resources On-Line Spatial
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Data12, have adopted semantic technologies or similar approaches to enrich the
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discoverability, accessibility and interoperability of data services. Those efforts create
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the space for exploring methods towards smart geoscience data and conducting
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studies on information retrieval and knowledge discovery.
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https://www.w3.org/XML/ https://www.w3.org/RDF/ 3 https://www.w3.org/TR/rdf-schema/ 4 https://www.w3.org/2004/02/skos/ 5 https://www.w3.org/OWL/ 6 http://www.opengeospatial.org/standards/wfs 7 http://www.opengeospatial.org/standards/wms 8 http://www.opengeospatial.org/standards/wcs 9 http://www.onegeology.org/ 10 http://usgin.org/ 11 http://www.auscope.org.au/ 12 https://mrdata.usgs.gov/ 2
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ACCEPTED MANUSCRIPT Each ontology is the formal specification of the shared conceptualization of a domain
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of study (Gruber, 1995). In the approach from big data to smart data, ontologies can
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take an effective role to deal with the data heterogeneity through semantic enrichment
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and concept mapping (Buccella et al., 2009; Duong et al., 2017; Sheth, 2014b;
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Sotnykova et al., 2005; Su and Gulla, 2004). Mark et al. (2001) discussed that
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ontologies can be categorized into geographic and conventional topics from the point
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of view of geographers. In the domain of geosciences, we would say the focus of
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geographic ontologies in Mark et al. (2001) is spatial information (cf. Buccella et al.,
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2009; Buccella et al., 2011; Ma et al., 2011; Visser, 2005), and the conventional
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ontologies are about domain-specific topics in geosciences, such as geologic time
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scale (Cox, 2011; Cox and Richard, 2005; Ma et al., 2012; Ma and Fox, 2013),
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geological modelling (Mastella et al.,2007; Perrin et al., 2005), geological structure
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(Zhong et al., 2009), and rock deformation (Babaie and Davarpanah, 2018). Detailed
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information about concepts and relationships within a focused domain can lead to
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innovative functions in smart geoscience data, and will provide solid support to
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geoscience researchers in data discovery and analysis.
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The objective of this research is building an ontology for a local geologic time
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standard and using it as a middle-ware to integrate and present information from
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multiple sources that is hard to retrieve by using existing methods. In this work, we
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first built an ontology for the local geologic time scale in North America. Second, we
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developed an interactive visualization for the ontology. Third, we deployed the
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backgrounds, and we conducted case studies of focused topics. We developed
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functions to implement the visualized ontology for interactive information query and
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browsing on the user interface. To our knowledge, the work is the first example of
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using a local geologic time scale ontology and data visualization to conduct efficient
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and smart information retrieval. The presented research not only benefits the
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integration and comparison of geologic time and fossil information, but also provides
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practical experience on how to analyze and address the gaps between cross-domain
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open data.
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The remainder of this paper is organized as follows: Section 2 describes the key
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methods and technologies deployed in this research. Section 3 describes the
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implementation of a pilot system and results. Section 4 analyzes the advantages and
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limits of this study, and proposes a few topics for the future work. Finally, Section 5
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gives a brief conclusion.
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2 Methods and Technologies
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Geoscience is a discipline with heterogeneous terminologies being used in its various
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sub-domains (Reitsma and Albrecht, 2005; Ma, 2015). This situation is also reflected
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in the geoscience data. If a user is not familiar with the terminology used in a dataset,
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it is hard for him to understand and use the data. There are already international
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efforts on coordinating schemas, ontologies and vocabularies in geoscience, such as
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within the International Union of Geological Sciences (CGI-IUGS)13. Nevertheless,
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there is limited work on ontologies and vocabularies of local and regional standards.
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On the other hand, legacy geoscience datasets are increasingly made accessible online
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and many of them contain conceptual models or terminologies that are not part of
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global standards. There are implicit connections between the local and global
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standards, but in most cases we are short of a machine-readable model to represent
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and describe such connections.
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Seeing both challenges and opportunities in the situation described above, we
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designed and implemented a pilot study of ontology-driven data integration and
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exploration focused on the local geologic time scale in North America. Technological
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components included an ontology for the local geologic time scale, visualization of
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the ontology, interfaces for accessing fossil occurrence records and geologic map
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services, and interactive functions that use the ontology to support users to understand
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and use datasets retrieved from multiple sources.
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2.1 An ontology for the local geologic time scale of North America
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The geologic time scale, a contiguous framework of time intervals, is a system using
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knowledges from stratigraphy, chronostratigraphy and paleontology to study the
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Earth’s planet history (Gradstein et al., 2012). A global geologic time scale standard is
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that standard, the lower boundaries of time intervals are in the process of being
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defined by the Global Boundary Stratotype Section and Points (GSSP). In the global
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geologic time scale, stage/age is the unit at the lowest level. The global stages are
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defined by a continuous rock unit that contains biologic, geochemical, magnetic or
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other methods for global correlation. Once a GSSP is defined, it will be marked as a
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“Golden Spike”.
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Although the global standard has been accepted by geoscience researchers across the
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world, national and regional geological surveys also refer to local geologic time
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standards of tectono-stratigraphic divisions. For example, the local geologic time
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scale in North America is established according to the specific strata sequences and
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geologic evolution history of the region. There are three major differences between
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them: (1) Different nomenclature and definition of intervals on the levels of Epoch
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and Age. The geologic time scale in North America inherits the global standard on the
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levels of Eon, Era, and Period, and establishes its unique standard on the levels of
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Epoch and Age. Therefore, the divisions of Eon, Era and Period are identical in the
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global and the North America standards. (2) Different start and end boundaries
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between high- and low-level intervals in the local standard. In the global standard,
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boundaries are coordinated, so high-level geologic time intervals usually share the
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start and end boundaries with their low-level intervals (Fig. 1a). Some geologic time
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the Period intervals, which results in “cross-boundary” patterns in the local geologic
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time scale (Fig. 1a, Fig. 4). (3) There are some unnamed intervals in the geologic time
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scale of North America (Fig. 1b, Fig. 3). There could be many reasons for this
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situation. For example, one reason could be the strata absence caused by sediment
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hiatus in a period of geologic time, such as the absence of Triassic and Jurassic strata
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(Brenner and Peterson, 1994). In another situation, although strata developed in the
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geologic time, the limited work on nomenclature could also result in the unnamed
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intervals. For example, the Devonian Period has named intervals on the Age level but
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lacks intervals on the Epoch level. (Fig. 1b, Fig. 4).
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Fig. 1 Comparison between global and North America geologic time standards. (a)
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shows the “cross-boundary” pattern. In the global standard, intervals at the Period,
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Epoch and Age levels share start and end boundaries in a coordinated framework. The
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divided intervals of Epoch and Age in the local standard of the North America are
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outside of such a framework and do not share boundaries with intervals in the global 8
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standard. (b) shows the interval without named intervals (missing data) on the Epoch
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level in the local standard of the North America. The data used in this figure are from
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Gradstein et al., (2012).
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170 The geologic time scale has both a hierarchal conceptual structure and an ordinal
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temporal sequence (Cox and Richard, 2005; Michalak, 2005). Previous studies of
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geologic time ontologies were mostly relevant to the semantic representation of the
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global standard recommended by the ICS (Cox, 2011; Cox and Richard, 2015; Ma
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and Fox, 2013). In those works, Semantic Web languages and schemas such as OWL,
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RDF and SKOS were used to encode the hierarchal structure and ordinal sequence
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(Cox and Richard, 2015; Ma et al., 2011; Ma and Fox, 2013). In this paper, we used
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the JavaScript Object Notation for Linked Data (JSON-LD)15, a lightweight
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data-interchange format based on the JavaScript Object Notation (JSON) to serialize
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Linked Data and encode the hierarchal structure and temporal sequence of the local
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geologic time scale of North America (Fig. 2). We referred to three major sources
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(Haq, 2007; Rohde, 2005; TSCreator, 2017) for the list of local geologic time
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intervals, their time boundaries, and the global-local geologic time interval mappings.
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In particular, for Triassic and Jurassic there are no recorded intervals at Epoch and
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Age levels in the North America standards. To avoid a big gap in the time scale, we
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used those intervals of Triassic and Jurassic from the global standards. For the
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encoding part, we wrote the JSON-LD file of the ontology manually. The JSON-LD
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file is accessible through the GitHub repository of this research16.
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Fig. 2 Part of JSON-LD code for representing hierarchal structure and temporal
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sequence in the local geologic time scale of North America. (a) shows the code of a
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“cross-boundary” pattern. The geologic time interval that crosses the boundary of two
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parent nodes was divided into two sub-objects by the boundary. The two sub-objects
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both inherit the same properties of the geologic time interval. (b) shows the code of an
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unnamed geologic time interval. It was represented in a record without a node name.
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Meaning of keywords: oid: object ID; name: node name of a geologic time interval;
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rank: era rank; base: the start time boundary; top: the end time boundary; mid: the
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middle of a geologic time interval; interval: time duration of geologic time interval. (c)
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shows the definition of “context” in the JSON-LD encoding, which maps the
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keywords to defined concepts in other existing ontologies and schemas.
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The properties were recorded in the braces and divided by commas. We employed the
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bracket, colon, and default keyword “children” of JSON-LD to encode the hierarchal
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structure of the geologic time scale. In the JSON-LD grammar, every node only has
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one parallel parent node. In this research, a geologic time interval crossing the
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boundary of two parent nodes was divided into two sub-objects by the boundary, and
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the two sub-objects both inherit the same properties of that interval (Fig. 2a). To
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create a complete framework for the ordinal-hierarchical structure, the unnamed
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intervals were encoded by records with an empty node name (Fig. 2b), and they have
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properties such as the start and end boundaries. To improve the interoperability of the
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developed ontology, the “context” (Fig. 2c) maps the keywords to IRIs
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(Internationalized Resource Indicator) of defined concepts in existing ontologies and
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schemas.
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2.2 Retrieving multi-source and multi-disciplinary geoscience data
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The Paleobiology Database (PBDB)17 is an open database of paleontological data
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(Peters and McClennen, 2015; Peters et al., 2014; Varela et al., 2015), which includes
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184, 259 collections, 350, 487 taxa and 1,325,725 occurrences in early March, 2017.
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It provides two types of data services: (1) explore the fossil information through a 17
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PBDB API (Application Program Interface). The former is for human users and the
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latter is for machines. In this work, we developed functions to use information of the
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named intervals in the local geologic time ontology of North America to retrieve
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fossil information (e.g. fossil occurrence location , accepted name, taxonomy,
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formation, reference, etc.) through the PBDB API. To enable the integration of more
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information, the retrieved fossil information was displayed together with geologic and
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geographic base maps. We developed functions to set up connections between the
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ontology and those data sources so they can be queried and compared interactively.
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The Web Map Service18 (WMS) is a standard protocol released by the Open
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Geospatial Consortium (OGC) for building geospatial data services on the Web. It is
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widely used in the web GIS application development for setting up geospatial data
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services, including geologic data. The Mineral Resources On-Line Spatial Data is an
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open database developed by the USGS mineral program. It provides data services of
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mineral resource, geology, geochemistry, geophysics, and more. WMS is one of the
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many standards applied by that database. In this work, we utilized the WMS “GetMap”
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and “GetFeatureInfo” functions to obtain the geologic map and feature properties
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from the USGS database, respectively. The retrieved information was used as a
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background map for the fossil information retrieved from PBDB. By integrating all
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those datasets, the developed system enables interested researchers to explore further
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geologic information of a focused area.
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fundamental geology
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A specific function enabled by ontologies is the semantic inference which can reveal
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new information and knowledge in a cross-domain context (Katifori et al., 2007). For
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each specific science domain, there are characteristic entities, properties and
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organizational structures that can be used in semantic reasoning and inference.
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Paleontology covers topics of taxon, position, location, age, fossil strata, source
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reference, and more. Fundamental geology, as revealed by a geologic map, usually
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contains geologic units, boundary, age, lithology, strata, color, location and reference
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information. Geologic time scale includes topics of age, early age, late age, duration
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time, as well as the hierarchal conceptual structure and the temporal sequence
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reflected in those concepts.
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map service. Paleo: paleontology; GTS: geologic times-scale; GM: geologic map
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service. The bold lines show the path used in this work to connect the Paleo, GM and
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GTS together.
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With the help of the developed ontology, the common concepts among geologic time
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scale, paleontology and geology were used to set up connections among the several
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resources in this study (Fig. 3). Although there are several paths to link them together,
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we selected the GTS-Age-Paleo-Location-GM route (bold solid line in Fig. 3) to build
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the pilot system for information retrieval and knowledge discovery in this work. The
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chosen route contains topics of time, location, fossil and fundamental geology, which
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make it and is a good case study to make use of all the data resources and conduct
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further exploration.
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3 Implementation, Prototype System and Results
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3.1 Interactive visualization for the local geologic time ontology of North America
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To visualize a geologic time ontology, a good way is needed for representing both the
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hierarchical conceptual structure and the ordinal time sequence (Cox, 2011; Cox and
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Richard, 2005; Ma et al., 2012; Ma and Fox, 2013). In previous works, both
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ActionScript and JavaScript languages have been used to visualize the global geologic
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time scale ontology (Ma et al., 2012; Ma et al., 2016). To get a human-friendly
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geologic time scale ontology of North America as an interactive partition displaying
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the hierarchical structure, temporal sequence, and annotation of geologic time
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intervals. D320 (Data-Driven Documents), an open-source JavaScript library to
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produce dynamic, interactive data visualization, was used as the basic library in the
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visualization. The resulting visualization was in JavaScript-driven SVG (Scalable
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Vector Graphics) format, which provided a functional tool to deploy the JSON-LD
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file of the ontology in an interactive web application (cf. Stefani et al., 2014).
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The resulting visualization shows the hierarchical and ordinal relationship of geologic
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time intervals (Fig. 4). The nodes laying out from the left to right follow the Earth’s
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history from the earlier to later. The width of every node represents the time duration
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of the corresponding geologic time interval, which is read from the JSON-LD records.
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From top to bottom, the hierarchical structure represents the node levels decrease
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from the Eon in the first layer to Age in the fifth layer. The name of a node is
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annotated on the node partition, which will be displayed when the node partition
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zooms in and gets enough space for the text of the name, and will be hidden when the
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node partition zooms out (Fig. 4).
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Fig.4 Interactive visualization of the local geologic time scale ontology of North
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America.
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We developed a user-friendly pilot system21 that connects elements from geologic
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time scale, paleontology, and WMS geologic map service together. The interface is
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showed in Fig. 5. It includes the visualized geologic time scale ontology at the bottom,
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a main window in the center displaying geologic and geographic base maps and fossil
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locations, radio buttons at the top left corner for choosing layers for further
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information query, a dropdown list to change the map window to different states in
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U.S., and dynamic pop-up windows for displaying query results.
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Fig.5 User interface of developed pilot system. (a) shows the blank area in a geologic
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map layer; (b) “undefined” formation indicates there is no information about the strata
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that contains the fossil; (c) and (d) show the information of the same area from the
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map layer and the fossil occurrence records, respectively. A topic of research interest
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here is the differences between the information in (c) and (d), which may lead to new
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studies about the area.
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The general workflow in the pilot system includes the following steps. First, a user
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can navigate in the ontology visualization to find an interval of interest. Second, the
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user can double click the node of the selected time interval, the system will retrieve
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the base and top time boundaries of that interval and send them to PBDB for
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records in the map window. There is also an information window on the top left
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corner of the map window to show the selected interval and the base and top time
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boundaries of it. Third, the user can use the radio buttons on the top left corner to
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choose the object layer (USGS geologic map or Fossil) for querying attribute
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information. For example, when the ‘USGS’ layer is selected, the user can retrieve the
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geologic information of a place on the map by a mouse click. When the ‘Fossil’ layer
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is selected, the user can click spots in the fossil occurrence layer to see attribute of
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fossils. The retrieved information is displayed in a mini pop-up window at the mouse
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click point. During the process, the user can also change the center of the map
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window to different states in the U.S. by making selections in a dropdown list at the
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top left.
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There are a few specific settings in the current pilot system. Through the PBDB API,
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abundant attributes of fossil occurrence records could be retrieved, but in the current
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system we only displayed a short list of information to compare with the geologic
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information from the USGS open dataset. In the map window, the geologic maps of
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different states will be automatically loaded when the zoom-in level of the window is
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8 or higher. The user can also zoom out to see the nationwide distribution of fossil
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occurrences in U.S., but the geologic map will disappear. To see the geologic map in
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the background, the user need to zoom in to a focused area to ensure the zoom-in
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level is higher than 8. To make the operation convenient, we created a dropdown list
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of states in U.S to help users select areas of interest. The geologic map of the selected
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state will be loaded automatically in the window.
348 Besides retrieving and integrating information from multiple sources, a more specific
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goal in this study is using the ontology for semantic connection, reasoning and
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knowledge discovery. In other words, we extracted the relevant datasets and then
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structured and connected them as “smart data” rather than listing them as separate
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items. Based on the retrieved information, we can use the semantic reasoning to
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obtain further information of an entity and its related entities. For example, we
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retrieved the fossil information within a period of time by using the start and end
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boundaries of named intervals from the geologic time ontology, rather than just using
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label match. Then, the fossil location information was used to retrieve the geologic
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map information from the USGS Mineral Resources On-Line Spatial Data, such as
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geologic unit, geologic age, petrology, and more. We were also able to compare the
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information from the different sources to find the similarities and differences (Fig. 5c
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and d).
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In the geologic time scale ontology, each geologic time interval is an entity linked
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with other entities. We can use the logical relationships in the ontology to find
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relevant entities within the geologic time scale. For example, Permian is not only a
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time interval from 298.9 Ma to 252.2 Ma (Gradstein et al., 2012), but is also a child
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node of Paleozoic, and the parent node of Wolfcampian, Leonardian, Guadalupian
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for information retrieval on the Web. For example, a user wants to find some typical
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records whose occurrence time are within the interval of Permian. If the time
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information is only recorded with the literal labels of geologic time intervals, then the
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search cannot be only done with the label ‘Permian’ but also the labels of the child
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intervals of Permian. The geologic time scale ontology can quickly provide all the
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child intervals of Permian. Such functions were developed in one of our previous
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studies (Ma et al., 2012).
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In this pilot system, the data source used for query is PBDB API, which provides
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several channels for querying fossil occurrence records within a period of time22. The
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first is through the input of the names of one or more geologic time intervals. The
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PBDB system has a collection of geologic time terms and their corresponding start
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and end time boundaries. If more than one label is input, then the time range used in
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the query will be the contiguous period from the start of the earliest interval to the end
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of the latest interval. The second query method in PBDB API is through the input of a
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maximum age and/or a minimum age. A key part of our work is the local geologic
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time scale of the North America. If we query with the names of time intervals in the
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built ontology, for some intervals (e.g. Wolfcampian or Leonardian) there will be no
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results. A possible reason is that those intervals are not included in the time term
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collection of PBDB or alternative names (e.g. the label ‘Wolfcamp’ in Fig. 5d) are
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the query function in the pilot system. When an interval is selected by the user (i.e.
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double click in the ontology visualization), a function will obtain the base and top
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boundaries of that interval in the ontology and then use them as input of maximum
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and minimum ages to query fossil occurrence records. For example, we could retrieve
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records from PBDB for Wolfcampian or Leonardian through this function.
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In this study, we used JSON-LD to encode the geologic time scale ontology of North
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America, which proves the functionality of JSON-LD as a Human-Machine readable
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and lightweight data-interchange format. We used the JSON-LD syntax, such as
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braces, brackets and default keywords to encode the hierarchal structure and temporal
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sequence of a geologic time ontology. More specifically, we used the “context” to
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map the keywords in our ontology to IRIs of defined concepts in other existing
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ontologies. In previous works, XML, OWL and SKOS have been used to encode the
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geologic time scale ontologies (Raskin and Pan, 2005; Cox and Richard, 2005; Ma et
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al. 2011; Ma et al., 2012; Ma and Fox, 2013). Compared with these works, the
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JSON-LD code for geologic time scale ontology is a concise format for data
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visualization, and can be used directly in the development of the user interface of
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applications.
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objects were added in the developed JSON-LD file. For example, as described in
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section 2.1, two sub-objects of a geologic time interval were used to describe the
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“cross-boundary” pattern and they both inherited the same properties of that interval.
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While this helps layout the ordinal-hierarchical structure in the resulting visualization,
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the two sub-object intervals are identical, which may lead to potential issues in logic
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reasoning. For example, in this research the operations on the visualized ontology
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were limited to single click for zooming into an interval and double click for querying
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fossil occurrences within the time coverage of an interval. The data structure and the
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content of the JSON-LD file met the needs of those operations. But for some other
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operations, such as querying the number of intervals at the Epoch level, the
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above-mentioned specific objects in the JSON-LD file will lead to incorrect results.
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One approach for addressing this issue is to have separate ontologies to store precise
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information, and then build the JSON-LD file for visualization as a compatible
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adaptation from those ontologies (cf. Ma et al. 2016; Ma 2017).
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As shown in the context of the JSON-LD file (Fig. 2c), this ontology was built on the
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top of a few other existing ontologies developed by Cox and Richard (2015). The
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focus of this research was the intervals in the local geologic time scale of the North
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America and their mappings to the global geologic time scale. The resulting
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JSON-LD file contained just the key information that addresses the needs of ontology
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visualization and fossil information retrieval in the pilot system. In our previous
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the geologic time scale (Ma et al., 2012), and we had planned similar works in this
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research. For example, in the developed pilot system if a user selects (i.e., double
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click) ‘Permian’ to find fossil occurrence records in PBDB, there could be a function
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to find all the child intervals of ‘Permian’ and use them together with ‘Permian’ as
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input for query. However, in this research we found that some intervals in the local
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geological time scale of the North America could not be recognized by PBDB.
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Therefore, instead of using the logic relationships between the time intervals, we just
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obtained the based and top time boundaries of a selected interval from the ontology
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and then use them in the query sent to PBDB.
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A driving force of this study is the feedbacks (personal communication) from
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geoscientists on our previous works (Ma et al., 2012; Ma et al., 2016). From
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conversations with colleagues in the field of paleontology, geobiology and
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stratigraphy, we found that Web applications with visualized geoscience knowledge
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and map services are useful in their research and teaching work. A suggestion from
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Prof. Miriam Katz on the visualization was that a horizontal or vertical layout is more
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familiar to geoscientists than the sunburst layout in our previous work, and this pilot
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system realized that layout. The system and a tutorial document were accessible
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online (see footnote 21), and the source code of the system was also published23. We
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will continuously collect feedbacks and suggestions from colleagues, especially
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geoscientists, and improve the functions of the system.
454 A well-organized ontology model is an efficient interface to link different research
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domains and this poses a lot of potential for geoscience research. In this study, we
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used the ontology model to link the structured data between geologic time scale,
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paleontology and fundamental geology, and set up the functions of information
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retrieval and inference. It was not our intention to redesign the wheel of the existing
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functions in PBDB, but the collected intervals for the local geologic time scale of the
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North America could complement the time term collection in PBDB. We also have a
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plan to encode more local geologic time standards such as those listed in Haq (2007)
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into formats for the Semantic Web and use them to build applications for querying
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open data on the Web.
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Among the various open geoscience data on the Web, a topic of interest is to explore
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the background of gaps among different data sources and study ways to bridge the
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gaps in data integration. In this research, several gaps in the cross-domain open data
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were found: (1) Data missing - there are empty properties for the fossil occurrences
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and blank areas for the WMS geologic map (Fig. 5a and b). (2) Synonym expression -
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there are significant differences in the Epoch and Age division and nomenclature of
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geologic time scale between global and North America standards. (3) The
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paleontology research and geologic mapping service refer to different geologic time
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same object (e.g. rock age, lithology) between PBDB and USGS databases (Fig. 5c
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and d). There could be many reasons for such differences, and a further study of the
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background information may lead to new topics for research. For example, in Fig. 5c
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and d, the point on the geologic map is at the edge of eroding Permian sediments, so
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the fossils in that alluvial can include those from Permian.
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Some data gaps could be caused by the differences between local and global standards.
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Geological investigation and interpretation is a scientific domain with subjectivity.
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Geologic standards are designed to reduce the subjectivity and enhance the objectivity
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at a national or local scale. Nevertheless, massive separately developed standards
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raise challenges against data exchange at a global scale. To address this challenge, the
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standards could be made open and published in machine-readable formats. We urge
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more researches to encode local geologic data standards in Web-compatible formats
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and publish them online for reuse. Once a big number of those local standards are
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made openly accessible, calibrations and connections among those local standards as
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well as between local and global standards can be made to promote the
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interoperability of datasets.
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There are several concepts can be used to explore the relationships between geologic
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time scale, paleontology, and fundamental geology, as shown in Figure 3. They lay
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out the space for extending and improving the developed system in the future. For
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example, in the developed pilot system, we used GTS-Age-Paleo-Location-GM route
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to implement the functions of information retrieve and reasoning. We also can use
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other routes to implement similar functions and conduct bidirectional query.
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and several future works can be proposed. The first is to collect more local geologic
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time standards, match them with the global geologic time standard, and use them to
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enrich the built ontology. The pilot study in this paper is an example about the local
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geologic time standard of North America. If the ontology is enriched with more local
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geologic time standards, it will be more useful in data search and integration on the
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Web. The second is to enrich the interactive functions on the user interface. This
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include the ontology content, the visualization, the map window operations, and the
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rendering and display of multisource information, such as geologic maps and fossil
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occurrence records. We will invite colleagues in the geoscience community to use the
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pilot system and provide feedbacks, then we will revise the system for its next version.
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Beside user feedback, we also plan a few other updates. For example, in addition to
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the visualized ontology, we can also build a free text and time boundary search, so a
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user can input a time term or two numeric time boundaries to search fossil occurrence
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records.
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5 Conclusion
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ACCEPTED MANUSCRIPT Geologic data have been increasingly made open online, while methods and tools to
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obtain knowledge from them are underdeveloped. Based on the open geologic data,
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we employed an ontology model to design and implement a pilot system crossing the
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domains of local geologic time scale of North America, paleontology, and
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fundamental geology. The pilot system (http://www2.cs.uidaho.edu/~max/gts/)
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realized the following functions: visualization of the geologic time ontology of North
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America, interactive fossil information retrieving and displaying, and query and
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comparison of fossil information and geologic map information. It is an interactive
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and integrated system for fossil, geologic map service, and geologic time scale of
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North America, and is proved useful in helping researchers explore information of
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interest and propose new research topics.
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The compatibility between local and global geoscience standards and gaps between
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different data sources will be a long-term challenge for the application of ontology
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models in geoscience knowledge discovery. To address these challenges, it is
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necessary to extend and improve the existing geologic ontology models to address
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broad compatibility, and call for more ontologies of local data standards (e.g. those
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listed in Haq, 2007 and Rohde, 2005) being developed and connected to improve the
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interoperability of datasets from different sources.
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Acknowledgement
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This work was partly supported by the National Science Foundation (NSF) through the NSF Idaho EPSCoR Program (award number IIA-1301792) and the W. M. Keck 27
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Foundation through the grant “The Co-Evolution of the Geo- and Biospheres: An Integrated Program for Data-Driven Abductive Discovery in Earth Sciences”. We thank USGS and Geophysical Laboratory at Carnegie Institution for Science for financial supports to our attendance at the 2017 USGS-DTDI workshop at Reston, VA. We also thank two anonymous reviewers and the editor Prof. Gregoire Mariethoz for their constructive comments on an earlier version of the manuscript.
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Build and visualize an ontology for the local geologic time scale of North America Ontology-driven retrieval and display of fossil occurrences and geologic maps Multi-source information query and comparison to enable exploratory analysis A successful case study towards smart geoscience data service
