A posteriori metadata from automated provenance tracking: Integration of AiiDA and TCOD

In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges that make this process difficult to achieve in practice. Here the implementation of a protocol is presented to tag crystal structures with their computed properties, without the need of human intervention to curate the data. This protocol leverages the capabilities of AiiDA, an open-source platform to manage and automate scientific computational workflows, and TCOD, an open-access database storing computed materials properties using a well-defined and exhaustive ontology. Based on these, the complete procedure to deposit computed data in the TCOD database is automated. All relevant metadata are extracted from the full provenance information that AiiDA tracks and stores automatically while managing the calculations. Such a protocol also enables reproducibility of scientific data in the field of computational materials science. As a proof of concept, the AiiDA-TCOD interface is used to deposit 170 theoretical structures together with their computed properties and their full provenance graphs, consisting in over 4600 AiiDA nodes

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

EU-Raw Materials Intelligence Capacity Platform (EU-RMCP) – Technical system specification

EU-Raw Materials Intelligence Capacity Platform (or EU-RMICP) integrates metadata on data sources related to primary and secondary mineral resources and brings the end users an expertise on the methods and tools used in mineral intelligence. The system is capable of bringing relevant user ‘answers’ of the type 'how to proceed for …' on almost any question related to mineral resources, on the whole supply chain, from prospecting to recycling, taking into account the environmental, political and social dimensions. EU-RMICP is based on an ontology of the domain of mineral resources (coupled with more generic cross-functional ontologies, relative to commodities, time and space), which represents the domain of the questions of the users (experts and non-experts). The user navigates in the ontology by using a Dynamic Graph of Decision (DDG), which allows him/her to discover the solutions which he/she is looking for without having to formulate any question. The system is coupled with a 'RDF Triple Store' (a database storing the ontologies), factSheets, doc-Sheets and flowSheets (i.e., specific formatted forms) related to methods and documentation, scenarios and metadata.JRC.B.6-Digital Econom

Data geo-Science Approach for Modelling Unconventional Petroleum Ecosystems and their Visual Analytics

Storage, integration and interoperability are critical challenges in the unconventional exploration data management. With a quest to explore unconventional hydrocarbons, in particular, shale gas from fractured shales, we aim at investigating new petroleum data geoscience approaches. The data geo-science describes the integration of geoscience-domain expertise, collaborating mathematical concepts, computing algorithms, machine learning tools, including data and business analytics. Further, to strengthen data-science services among producing companies, we propose an integrated multidimensional repository system, for which factual instances are acquired on gas shales, to store, process and deliver fractured-data views in new knowledge domains. Data dimensions are categorized to examine their suitability in the integrated prototype articulations that use fracture-networks and attribute dimension model descriptions. The factual instances are typically from seismic attributes, seismically interpreted geological structures and reservoirs, well log, including production data entities. For designing and developing multidimensional repository systems, we create various artefacts, describing conceptual, logical and physical models. For exploring the connectivity between seismic and geology entities, multidimensional ontology models are construed using fracture network attribute dimensions and their instances. Different data warehousing and mining are added support to the management of ontologies that can bring the data instances of fractured shales, to unify and explore the associativity between high-dense fractured shales and their orientations. The models depicting collaboration of geology, geophysics, reservoir engineering and geo-mechanics entities and their dimensions can substantially reduce the risk and uncertainty involved in modelling and interpreting shale- and tight-gas reservoirs, including traps associated with Coal Bed Methane (CBM). Anisotropy, Poisson's ratio and Young's modulus properties corroborate the interpretation of stress images from the 3D acoustic characterization of shale reservoirs. The statistical analysis of data-views, their correlations and patterns further facilitate us to visualize and interpret geoscientific metadata meticulously. Data geo-science guided integrated methodology can be applied in any basin, including frontier basins

On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management

Establishing the reservoir connections is paramount in exploration and exploitation of unconventional petroleum systems and their reservoirs. In Big Data scale, multiple petroleum systems hold volumes and varieties of data sources. The connectivity between petroleum reservoirs and their existence in a single petroleum ecosystem is often ambiguously interpreted. They are heterogeneous and unstructured in multiple domains. They need better data integration methods to interpret the interplay between elements and processes of petroleum systems. Largescale infrastructure is needed to build data relationships between different petroleum systems. The purpose of the research is to establish the connectivity between petroleum systems through resource data management and visual analytics. We articulate a Design Science Information System (DSIS) approach, bringing various artefacts together from multiple domains of petroleum provinces. The DSIS emerges as a knowledge-based digital ecosystem innovation, justifying its need, connecting geographically controlled petroleum systems and building knowledge of oil and gas prospects

Semantic linking of complex properties, monitoring processes and facilities in web-based representations of the environment

Where a virtual representation of the Earth must contain data values observed within the physical Earth system, data models are required that allow the integration of data across the silos of various Earth and environmental sciences domains. Creating a mapping between the well-defined terminologies of these silos is a stubborn problem. This paper presents a generalised ontology for use within Web 3.0 services, which builds on European Commission spatial data infrastructure models. The presented ontology acknowledges that there are many complexities to the description of environmental properties which can be observed within the physical Earth system. The ontology is shown to be flexible and robust enough to describe concepts drawn from a range of Earth science disciplines, including ecology, geochemistry, hydrology and oceanography. This paper also demonstrates the alignment and compatibility of the ontology with existing systems and shows applications in which the ontology may be deployed

Spatial Ontology for the Production Domain of Petroleum Geology

ABSTRACT The availability of useful information for research strongly depends on well structured relationships between consistently defined concepts (terms) in that domain. This can be achieved through ontologies. Ontologies are models of the knowledge of specific domain such as petroleum geology, in a computer understandable format. Knowledge is a collection of facts. Facts are represented by RDF triples (subject-predicate-object). A domain ontology is therefore a collection of many RDF triples, which represent facts of that domain. The SWEET ontologies are upper or top-level ontologies (foundation ontologies) consisting of thousands of very general concepts. These concepts are obtained from of Earth System science and include other related concepts. The work in this thesis deals with scientific knowledge representation in which the SWEET ontologies are extended to include wider, more specific and specialized concepts used in Petroleum Geology. Thus Petroleum Geology knowledge modeling is presented in this thesis

Tsunami-Related Data: A Review of Available Repositories Used in Scientific Literature

Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management

An ontology of the physical geography of Portugal

Tese de mestrado, Engenharia Geográfica e Geoinformática (Sistemas de Informação Geográfica), Universidade de Lisboa, Faculdade de Ciências, 2009Com o advento da Web Semântica é cada vez mais premente desenvolver novas formas de partilha de conhecimento que melhorem a interoperabilidade entre sistemas de informação geográfica (SIG). A modelação e representação do conhecimento geográfico sob a forma ontológica é uma das novas possibilidades. Esta dissertação estende uma representação ontológica, de acesso livre da geográfica de Portugal, a Geo-Net-PT01, acrescentando-lhe, aos já caracterizados domínios da geografia humana e da web portuguesa, o domínio da geográfica física. Para tal, foi incorporado no meta-modelo de informação pré-existente suporte para exprimir informação geográfica geo-referenciada numericamente. Desenvolveu-se uma metodologia para produção de modelos ontológicos incorporando o conhecimento do domínio da geografia física recorrendo ás fontes de produção de informação geográfica existentes. Esta metodologia foi utilizada na produção de uma nova versão da ontologia geográfica de Portugal, a Geo-Net-PT02, que agora incorpora dados sobre mais cerca de 24.000 entidades geo-referenciadas do território português.The advent of the Semantic Web raised the need for development of new methodologies for information sharing that improve interoperability among geographic information systems (GIS). The modeling and representation of geographic knowledge in the ontologic form is one of the new possibilities. This dissertation extends an open source representation of the geography of Portugal, Geo-Net-PT01, adding to the previously characterised domains of the human geography and the Portuguese Web, the domain of physical geography. To that purpose, the existing information meta-model was extended with support for expressing geo-referenced information in numeric form. A method for production of ontologic models incorporating the knowledge from physical geography from existing geographic information producers. This methodology was used in the production of a new version of the geographic ontology of Portugal, Geo-Net-PT02, which now incorporates data on over 24,000 geo-referenced entities in the Portuguese territory