�ݺ�ߣshows by User: MarshallXMa

�ݺ�ߣshows by User: MarshallXMa / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: MarshallXMa / Mon, 19 Oct 2015 20:42:09 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: MarshallXMa From data portal to knowledge portal: Leveraging semantic technologies to support interdisciplinary studies /slideshow/from-data-portal-to-knowledge-portal-leveraging-semantic-technologies-to-support-interdisciplinary-studies/54138102 2015diversitydco-151019204209-lva1-app6892
Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the data, code, sample collections and publications, etc. freely accessible online. The other is the annotation and connection between those resources to establish the provenance information for reproducible scientific research. In this paper we present our work on a web portal for the Deep Carbon Observatory (DCO) community. The DCO is a 10-year (2009-2019) initiative to intensify global attention and scientific effort in the burgeoning field of deep carbon science. Inspired by guiding questions such as “how much carbon does Earth contain?”, “where is it?” and “what can deep carbon tell us about origins?” more than 1000 scientists across the world are actively participating in the DCO community. The DCO web portal is a research collaboration website developed to keep track of all researchers, organizations, instruments, field sites, and research outputs related to the DCO community. We intend for the DCO web portal to be a knowledge portal - adopting state-of-the-art semantic technologies to support various stages of the scientific process within and beyond the DCO community.]]>
Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the data, code, sample collections and publications, etc. freely accessible online. The other is the annotation and connection between those resources to establish the provenance information for reproducible scientific research. In this paper we present our work on a web portal for the Deep Carbon Observatory (DCO) community. The DCO is a 10-year (2009-2019) initiative to intensify global attention and scientific effort in the burgeoning field of deep carbon science. Inspired by guiding questions such as “how much carbon does Earth contain?”, “where is it?” and “what can deep carbon tell us about origins?” more than 1000 scientists across the world are actively participating in the DCO community. The DCO web portal is a research collaboration website developed to keep track of all researchers, organizations, instruments, field sites, and research outputs related to the DCO community. We intend for the DCO web portal to be a knowledge portal - adopting state-of-the-art semantic technologies to support various stages of the scientific process within and beyond the DCO community.]]> Mon, 19 Oct 2015 20:42:09 GMT /slideshow/from-data-portal-to-knowledge-portal-leveraging-semantic-technologies-to-support-interdisciplinary-studies/54138102 MarshallXMa@slideshare.net(MarshallXMa) From data portal to knowledge portal: Leveraging semantic technologies to support interdisciplinary studies MarshallXMa Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the data, code, sample collections and publications, etc. freely accessible online. The other is the annotation and connection between those resources to establish the provenance information for reproducible scientific research. In this paper we present our work on a web portal for the Deep Carbon Observatory (DCO) community. The DCO is a 10-year (2009-2019) initiative to intensify global attention and scientific effort in the burgeoning field of deep carbon science. Inspired by guiding questions such as “how much carbon does Earth contain?”, “where is it?” and “what can deep carbon tell us about origins?” more than 1000 scientists across the world are actively participating in the DCO community. The DCO web portal is a research collaboration website developed to keep track of all researchers, organizations, instruments, field sites, and research outputs related to the DCO community. We intend for the DCO web portal to be a knowledge portal - adopting state-of-the-art semantic technologies to support various stages of the scientific process within and beyond the DCO community. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015diversitydco-151019204209-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the data, code, sample collections and publications, etc. freely accessible online. The other is the annotation and connection between those resources to establish the provenance information for reproducible scientific research. In this paper we present our work on a web portal for the Deep Carbon Observatory (DCO) community. The DCO is a 10-year (2009-2019) initiative to intensify global attention and scientific effort in the burgeoning field of deep carbon science. Inspired by guiding questions such as “how much carbon does Earth contain?”, “where is it?” and “what can deep carbon tell us about origins?” more than 1000 scientists across the world are actively participating in the DCO community. The DCO web portal is a research collaboration website developed to keep track of all researchers, organizations, instruments, field sites, and research outputs related to the DCO community. We intend for the DCO web portal to be a knowledge portal - adopting state-of-the-art semantic technologies to support various stages of the scientific process within and beyond the DCO community.

From data portal to knowledge portal: Leveraging semantic technologies to support interdisciplinary studies from Xiaogang (Marshall) Ma

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0 Exploring the Web of Data for Earth and Environmental Sciences /slideshow/exploring-the-web-of-data-forearth-and-environmental-sciences/46640193 20150319mcgill-v2-150404110309-conversion-gate01
The presentation includes three parts: 1) a short introduction to semantic web and linked data; 2) a review of a few projects of interest in the field of earth science; and 3) details about the workflow and algorithms for computing similarity between entities in the semantic web.]]>
The presentation includes three parts: 1) a short introduction to semantic web and linked data; 2) a review of a few projects of interest in the field of earth science; and 3) details about the workflow and algorithms for computing similarity between entities in the semantic web.]]> Sat, 04 Apr 2015 11:03:09 GMT /slideshow/exploring-the-web-of-data-forearth-and-environmental-sciences/46640193 MarshallXMa@slideshare.net(MarshallXMa) Exploring the Web of Data for Earth and Environmental Sciences MarshallXMa The presentation includes three parts: 1) a short introduction to semantic web and linked data; 2) a review of a few projects of interest in the field of earth science; and 3) details about the workflow and algorithms for computing similarity between entities in the semantic web. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20150319mcgill-v2-150404110309-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The presentation includes three parts: 1) a short introduction to semantic web and linked data; 2) a review of a few projects of interest in the field of earth science; and 3) details about the workflow and algorithms for computing similarity between entities in the semantic web.

Exploring the Web of Data for Earth and Environmental Sciences from Xiaogang (Marshall) Ma

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0 Adoption of RDA DTR and PID in Deep Carbon Observatory Data Portal /slideshow/20150308-rda-p5adoptiondcov1/45626537 20150308rda-p5adoptiondco-v1-150309152738-conversion-gate01
The Deep Carbon Observatory (DCO) community is building a cyber-enabled platform for linked science, made available to the community by a multi-institutional data portal. Persistent identifiers and domain specific data types have been identified as key technological issues the portal must address. This presentation focuses on the DCO portal’s planned adoption of RDA DTR and PID methodologies and technologies as a means to address the DCO community's need for persistently identifiable and understandable data type information.]]>
The Deep Carbon Observatory (DCO) community is building a cyber-enabled platform for linked science, made available to the community by a multi-institutional data portal. Persistent identifiers and domain specific data types have been identified as key technological issues the portal must address. This presentation focuses on the DCO portal’s planned adoption of RDA DTR and PID methodologies and technologies as a means to address the DCO community's need for persistently identifiable and understandable data type information.]]> Mon, 09 Mar 2015 15:27:38 GMT /slideshow/20150308-rda-p5adoptiondcov1/45626537 MarshallXMa@slideshare.net(MarshallXMa) Adoption of RDA DTR and PID in Deep Carbon Observatory Data Portal MarshallXMa The Deep Carbon Observatory (DCO) community is building a cyber-enabled platform for linked science, made available to the community by a multi-institutional data portal. Persistent identifiers and domain specific data types have been identified as key technological issues the portal must address. This presentation focuses on the DCO portal’s planned adoption of RDA DTR and PID methodologies and technologies as a means to address the DCO community's need for persistently identifiable and understandable data type information. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20150308rda-p5adoptiondco-v1-150309152738-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The Deep Carbon Observatory (DCO) community is building a cyber-enabled platform for linked science, made available to the community by a multi-institutional data portal. Persistent identifiers and domain specific data types have been identified as key technological issues the portal must address. This presentation focuses on the DCO portal’s planned adoption of RDA DTR and PID methodologies and technologies as a means to address the DCO community's need for persistently identifiable and understandable data type information.

Adoption of RDA DTR and PID in Deep Carbon Observatory Data Portal from Xiaogang (Marshall) Ma

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0 Knowledge Evolution in Distributed Geoscience Datasets and the Role of Semantic Technologies /slideshow/knowledge-evolution-in-distributed-geoscience-datasets-and-the-role-of-semantic-technologies/45225717 agu2014xmalecture-s-150227084518-conversion-gate01
Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community’s concern that the International Commission on Stratigraphy’s change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624.]]>
Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community’s concern that the International Commission on Stratigraphy’s change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624.]]> Fri, 27 Feb 2015 08:45:18 GMT /slideshow/knowledge-evolution-in-distributed-geoscience-datasets-and-the-role-of-semantic-technologies/45225717 MarshallXMa@slideshare.net(MarshallXMa) Knowledge Evolution in Distributed Geoscience Datasets and the Role of Semantic Technologies MarshallXMa Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community’s concern that the International Commission on Stratigraphy’s change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/agu2014xmalecture-s-150227084518-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community’s concern that the International Commission on Stratigraphy’s change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624.

Knowledge Evolution in Distributed Geoscience Datasets and the Role of Semantic Technologies from Xiaogang (Marshall) Ma

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0 Why Data Science Matters - 2014 WDS Data Stewardship Award Lecture /slideshow/why-data-science-matters/41108432 2014scidataconxmaawardlecture-141104092801-conversion-gate02
A presentation with a review of technical trends in data management, publication and citation, and methodologies on data interoperability, provenance of research and semantic escience.]]>
A presentation with a review of technical trends in data management, publication and citation, and methodologies on data interoperability, provenance of research and semantic escience.]]> Tue, 04 Nov 2014 09:28:01 GMT /slideshow/why-data-science-matters/41108432 MarshallXMa@slideshare.net(MarshallXMa) Why Data Science Matters - 2014 WDS Data Stewardship Award Lecture MarshallXMa A presentation with a review of technical trends in data management, publication and citation, and methodologies on data interoperability, provenance of research and semantic escience. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014scidataconxmaawardlecture-141104092801-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /> A presentation with a review of technical trends in data management, publication and citation, and methodologies on data interoperability, provenance of research and semantic escience.

Why Data Science Matters - 2014 WDS Data Stewardship Award Lecture from Xiaogang (Marshall) Ma

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0 Why data science matters and what we can do with it /slideshow/why-data-science-matters-and-what-we-can-do-with-it/37198547 xmadco-ss2014v2-140721092050-phpapp02
Presentation at the Deep Carbon Observatory Summer School 2014, Big Sky, MT, USA.]]>
Presentation at the Deep Carbon Observatory Summer School 2014, Big Sky, MT, USA.]]> Mon, 21 Jul 2014 09:20:50 GMT /slideshow/why-data-science-matters-and-what-we-can-do-with-it/37198547 MarshallXMa@slideshare.net(MarshallXMa) Why data science matters and what we can do with it MarshallXMa Presentation at the Deep Carbon Observatory Summer School 2014, Big Sky, MT, USA. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/xmadco-ss2014v2-140721092050-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation at the Deep Carbon Observatory Summer School 2014, Big Sky, MT, USA.

Why data science matters and what we can do with it from Xiaogang (Marshall) Ma

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0 Deep Earth Computer: A Platform for �Linked Science of �the Deep Carbon Observatory Community /slideshow/dco-ecs-2014crxmav2/31405566 dcoecs2014crxmav2-140219153856-phpapp01
Deep Carbon Observatory-Data Science is assembling a Deep Earth Computer for the Deep Carbon Observatory (DCO). The efforts will create a fundamental change in the conduct of Carbon-related research, resting upon a 21st century data science platform, and a series of aggregate data holdings that have never existed before. Data science combines aspects of informatics, data management, library science, computer science and physical science using cyberinfrastructure and information technology. The Deep Earth Computer we build provides these functions at minimum: an concept-type repository, an ability to identify and manage all key entities, agents and activities in the platform, a repository for archiving datasets and associated metadata, collaboration tools, and an integrated portal to manage diverse content and applications, with varied access levels and privacy options. The Deep Earth Computer sets up a platform for the Linked Science of the Deep Carbon Community, that is, not only scientific assets like data and methods behind scientific settings are opened and inter-connected, but also the people, organizations, groups, samples, instruments, activities, grants, meetings, etc. are recorded and inter-connected. Such a platform will promote collaborations among DCO community members, improve the openness and reproducibility of Carbon-related researches, and facilitate accreditation to resource (including publications, datasets, instruments, etc.) contributors. ]]>
Deep Carbon Observatory-Data Science is assembling a Deep Earth Computer for the Deep Carbon Observatory (DCO). The efforts will create a fundamental change in the conduct of Carbon-related research, resting upon a 21st century data science platform, and a series of aggregate data holdings that have never existed before. Data science combines aspects of informatics, data management, library science, computer science and physical science using cyberinfrastructure and information technology. The Deep Earth Computer we build provides these functions at minimum: an concept-type repository, an ability to identify and manage all key entities, agents and activities in the platform, a repository for archiving datasets and associated metadata, collaboration tools, and an integrated portal to manage diverse content and applications, with varied access levels and privacy options. The Deep Earth Computer sets up a platform for the Linked Science of the Deep Carbon Community, that is, not only scientific assets like data and methods behind scientific settings are opened and inter-connected, but also the people, organizations, groups, samples, instruments, activities, grants, meetings, etc. are recorded and inter-connected. Such a platform will promote collaborations among DCO community members, improve the openness and reproducibility of Carbon-related researches, and facilitate accreditation to resource (including publications, datasets, instruments, etc.) contributors. ]]> Wed, 19 Feb 2014 15:38:56 GMT /slideshow/dco-ecs-2014crxmav2/31405566 MarshallXMa@slideshare.net(MarshallXMa) Deep Earth Computer: A Platform for �Linked Science of �the Deep Carbon Observatory Community MarshallXMa Deep Carbon Observatory-Data Science is assembling a Deep Earth Computer for the Deep Carbon Observatory (DCO). The efforts will create a fundamental change in the conduct of Carbon-related research, resting upon a 21st century data science platform, and a series of aggregate data holdings that have never existed before. Data science combines aspects of informatics, data management, library science, computer science and physical science using cyberinfrastructure and information technology. The Deep Earth Computer we build provides these functions at minimum: an concept-type repository, an ability to identify and manage all key entities, agents and activities in the platform, a repository for archiving datasets and associated metadata, collaboration tools, and an integrated portal to manage diverse content and applications, with varied access levels and privacy options. The Deep Earth Computer sets up a platform for the Linked Science of the Deep Carbon Community, that is, not only scientific assets like data and methods behind scientific settings are opened and inter-connected, but also the people, organizations, groups, samples, instruments, activities, grants, meetings, etc. are recorded and inter-connected. Such a platform will promote collaborations among DCO community members, improve the openness and reproducibility of Carbon-related researches, and facilitate accreditation to resource (including publications, datasets, instruments, etc.) contributors. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dcoecs2014crxmav2-140219153856-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Deep Carbon Observatory-Data Science is assembling a Deep Earth Computer for the Deep Carbon Observatory (DCO). The efforts will create a fundamental change in the conduct of Carbon-related research, resting upon a 21st century data science platform, and a series of aggregate data holdings that have never existed before. Data science combines aspects of informatics, data management, library science, computer science and physical science using cyberinfrastructure and information technology. The Deep Earth Computer we build provides these functions at minimum: an concept-type repository, an ability to identify and manage all key entities, agents and activities in the platform, a repository for archiving datasets and associated metadata, collaboration tools, and an integrated portal to manage diverse content and applications, with varied access levels and privacy options. The Deep Earth Computer sets up a platform for the Linked Science of the Deep Carbon Community, that is, not only scientific assets like data and methods behind scientific settings are opened and inter-connected, but also the people, organizations, groups, samples, instruments, activities, grants, meetings, etc. are recorded and inter-connected. Such a platform will promote collaborations among DCO community members, improve the openness and reproducibility of Carbon-related researches, and facilitate accreditation to resource (including publications, datasets, instruments, etc.) contributors.

Deep Earth Computer: A Platform for Linked Science of the Deep Carbon Observatory Community from Xiaogang (Marshall) Ma

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0 CLOSED - Call for Papers: Semantic eScience special issue in Earth Science Informatics journal /slideshow/esin-se-scfp1/29912661 esinsescfp1-140111133348-phpapp01
This special issue invites research papers that demonstrate how semantic methodologies and technologies are currently meeting scientific or engineering goals in Earth and space science domains. Papers should highlight the innovative designs, methods or applications associated with the semantic technologies. Review papers presenting state-of-the-art knowledge about a subject in semantic e-Science and methodology and software papers about a new algorithm or software package are also welcome.]]>
This special issue invites research papers that demonstrate how semantic methodologies and technologies are currently meeting scientific or engineering goals in Earth and space science domains. Papers should highlight the innovative designs, methods or applications associated with the semantic technologies. Review papers presenting state-of-the-art knowledge about a subject in semantic e-Science and methodology and software papers about a new algorithm or software package are also welcome.]]> Sat, 11 Jan 2014 13:33:47 GMT /slideshow/esin-se-scfp1/29912661 MarshallXMa@slideshare.net(MarshallXMa) CLOSED - Call for Papers: Semantic eScience special issue in Earth Science Informatics journal MarshallXMa This special issue invites research papers that demonstrate how semantic methodologies and technologies are currently meeting scientific or engineering goals in Earth and space science domains. Papers should highlight the innovative designs, methods or applications associated with the semantic technologies. Review papers presenting state-of-the-art knowledge about a subject in semantic e-Science and methodology and software papers about a new algorithm or software package are also welcome. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/esinsescfp1-140111133348-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> This special issue invites research papers that demonstrate how semantic methodologies and technologies are currently meeting scientific or engineering goals in Earth and space science domains. Papers should highlight the innovative designs, methods or applications associated with the semantic technologies. Review papers presenting state-of-the-art knowledge about a subject in semantic e-Science and methodology and software papers about a new algorithm or software package are also welcome.

CLOSED - Call for Papers: Semantic eScience special issue in Earth Science Informatics journal from Xiaogang (Marshall) Ma

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0 Ontology Development for Provenance Tracing in �National Climate Assessment of �the US Global Change Research Program /slideshow/ontology-development-for-provenance-tracing-in-national-climate-assessment-of-the-us-global-change-research-program/29001040 agu2013xmagcis-v2-131207190410-phpapp01
The periodical National Climate Assessment (NCA) of the US Global Change Research Program (USGCRP) [1] produces reports about findings of global climate change and the impacts of climate change on the United States. Those findings are of great public and academic concerns and are used in policy and management decisions, which make the provenance information of findings in those reports especially important. The USGCRP is developing a Global Change Information System (GCIS), in which the NCA reports and associated provenance information are the primary records. We were modeling and developing Semantic Web applications for the GCIS. By applying a use case-driven iterative methodology [2], we developed an ontology [3] to represent the content structure of a report and the associated provenance information. We also mapped the classes and properties in our ontology into the W3C PROV-O ontology [4] to realize the formal presentation of provenance. We successfully implemented the ontology in several pilot systems for a recent National Climate Assessment report (i.e., the NCA3). They provide users the functionalities to browse and search provenance information with topics of interest. Provenance information of the NCA3 has been made structured and interoperable by applying the developed ontology. Besides the pilot systems we developed, other tools and services are also able to interact with the data in the context of the “Web of data” and thus create added values. Our research shows that the use case-driven iterative method bridges the gap between Semantic Web researchers and earth and environmental scientists and is able to be deployed rapidly for developing Semantic Web applications. Our work also provides first-hand experience for re-using the W3C PROV-O ontology in the field of earth and environmental sciences, as the PROV-O ontology is recently ratified (on 04/30/2013) by the W3C as a recommendation and relevant applications are still rare. [1] http://www.globalchange.gov [2] Fox, P., McGuinness, D.L., 2008. TWC Semantic Web Methodology. Accessible at: http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology [3] https://scm.escience.rpi.edu/svn/public/projects/gcis/trunk/rdf/schema/GCISOntology.ttl [4] http://www.w3.org/TR/prov-o/ ]]>
The periodical National Climate Assessment (NCA) of the US Global Change Research Program (USGCRP) [1] produces reports about findings of global climate change and the impacts of climate change on the United States. Those findings are of great public and academic concerns and are used in policy and management decisions, which make the provenance information of findings in those reports especially important. The USGCRP is developing a Global Change Information System (GCIS), in which the NCA reports and associated provenance information are the primary records. We were modeling and developing Semantic Web applications for the GCIS. By applying a use case-driven iterative methodology [2], we developed an ontology [3] to represent the content structure of a report and the associated provenance information. We also mapped the classes and properties in our ontology into the W3C PROV-O ontology [4] to realize the formal presentation of provenance. We successfully implemented the ontology in several pilot systems for a recent National Climate Assessment report (i.e., the NCA3). They provide users the functionalities to browse and search provenance information with topics of interest. Provenance information of the NCA3 has been made structured and interoperable by applying the developed ontology. Besides the pilot systems we developed, other tools and services are also able to interact with the data in the context of the “Web of data” and thus create added values. Our research shows that the use case-driven iterative method bridges the gap between Semantic Web researchers and earth and environmental scientists and is able to be deployed rapidly for developing Semantic Web applications. Our work also provides first-hand experience for re-using the W3C PROV-O ontology in the field of earth and environmental sciences, as the PROV-O ontology is recently ratified (on 04/30/2013) by the W3C as a recommendation and relevant applications are still rare. [1] http://www.globalchange.gov [2] Fox, P., McGuinness, D.L., 2008. TWC Semantic Web Methodology. Accessible at: http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology [3] https://scm.escience.rpi.edu/svn/public/projects/gcis/trunk/rdf/schema/GCISOntology.ttl [4] http://www.w3.org/TR/prov-o/ ]]> Sat, 07 Dec 2013 19:04:10 GMT /slideshow/ontology-development-for-provenance-tracing-in-national-climate-assessment-of-the-us-global-change-research-program/29001040 MarshallXMa@slideshare.net(MarshallXMa) Ontology Development for Provenance Tracing in �National Climate Assessment of �the US Global Change Research Program MarshallXMa The periodical National Climate Assessment (NCA) of the US Global Change Research Program (USGCRP) [1] produces reports about findings of global climate change and the impacts of climate change on the United States. Those findings are of great public and academic concerns and are used in policy and management decisions, which make the provenance information of findings in those reports especially important. The USGCRP is developing a Global Change Information System (GCIS), in which the NCA reports and associated provenance information are the primary records. We were modeling and developing Semantic Web applications for the GCIS. By applying a use case-driven iterative methodology [2], we developed an ontology [3] to represent the content structure of a report and the associated provenance information. We also mapped the classes and properties in our ontology into the W3C PROV-O ontology [4] to realize the formal presentation of provenance. We successfully implemented the ontology in several pilot systems for a recent National Climate Assessment report (i.e., the NCA3). They provide users the functionalities to browse and search provenance information with topics of interest. Provenance information of the NCA3 has been made structured and interoperable by applying the developed ontology. Besides the pilot systems we developed, other tools and services are also able to interact with the data in the context of the “Web of data” and thus create added values. Our research shows that the use case-driven iterative method bridges the gap between Semantic Web researchers and earth and environmental scientists and is able to be deployed rapidly for developing Semantic Web applications. Our work also provides first-hand experience for re-using the W3C PROV-O ontology in the field of earth and environmental sciences, as the PROV-O ontology is recently ratified (on 04/30/2013) by the W3C as a recommendation and relevant applications are still rare. [1] http://www.globalchange.gov [2] Fox, P., McGuinness, D.L., 2008. TWC Semantic Web Methodology. Accessible at: http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology [3] https://scm.escience.rpi.edu/svn/public/projects/gcis/trunk/rdf/schema/GCISOntology.ttl [4] http://www.w3.org/TR/prov-o/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/agu2013xmagcis-v2-131207190410-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The periodical National Climate Assessment (NCA) of the US Global Change Research Program (USGCRP) [1] produces reports about findings of global climate change and the impacts of climate change on the United States. Those findings are of great public and academic concerns and are used in policy and management decisions, which make the provenance information of findings in those reports especially important. The USGCRP is developing a Global Change Information System (GCIS), in which the NCA reports and associated provenance information are the primary records. We were modeling and developing Semantic Web applications for the GCIS. By applying a use case-driven iterative methodology [2], we developed an ontology [3] to represent the content structure of a report and the associated provenance information. We also mapped the classes and properties in our ontology into the W3C PROV-O ontology [4] to realize the formal presentation of provenance. We successfully implemented the ontology in several pilot systems for a recent National Climate Assessment report (i.e., the NCA3). They provide users the functionalities to browse and search provenance information with topics of interest. Provenance information of the NCA3 has been made structured and interoperable by applying the developed ontology. Besides the pilot systems we developed, other tools and services are also able to interact with the data in the context of the “Web of data” and thus create added values. Our research shows that the use case-driven iterative method bridges the gap between Semantic Web researchers and earth and environmental scientists and is able to be deployed rapidly for developing Semantic Web applications. Our work also provides first-hand experience for re-using the W3C PROV-O ontology in the field of earth and environmental sciences, as the PROV-O ontology is recently ratified (on 04/30/2013) by the W3C as a recommendation and relevant applications are still rare. [1] http://www.globalchange.gov [2] Fox, P., McGuinness, D.L., 2008. TWC Semantic Web Methodology. Accessible at: http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology [3] https://scm.escience.rpi.edu/svn/public/projects/gcis/trunk/rdf/schema/GCISOntology.ttl [4] http://www.w3.org/TR/prov-o/

Ontology Development for Provenance Tracing in National Climate Assessment of the US Global Change Research Program from Xiaogang (Marshall) Ma

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0 A short review of Connected China: A visualization of elite social networks in China /slideshow/20131101-e-sciencexma/27822115 20131101-esciencexma-131101161252-phpapp01
Features of Connected China Technologies in its development Potential updates]]>
Features of Connected China Technologies in its development Potential updates]]> Fri, 01 Nov 2013 16:12:52 GMT /slideshow/20131101-e-sciencexma/27822115 MarshallXMa@slideshare.net(MarshallXMa) A short review of Connected China: A visualization of elite social networks in China MarshallXMa Features of Connected China Technologies in its development Potential updates <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20131101-esciencexma-131101161252-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Features of Connected China Technologies in its development Potential updates

A short review of Connected China: A visualization of elite social networks in China from Xiaogang (Marshall) Ma

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0 Ontology spectrum for geological data interoperability (PhD defense nov 2011) /slideshow/ontology-spectrum-for-geological-data-interoperability-phddefence/27543928 ontologyspectrumforgeologicaldatainteroperabilityphddefence-131024152259-phpapp02
Ontology spectrum for geological data interoperability. A 10-minutre layman presentation for my PhD defense at University of Twente, 2011/11/30. Full text of dissertation is accessible at: http://www.itc.nl/library/papers_2011/phd/ma.pdf]]>
Ontology spectrum for geological data interoperability. A 10-minutre layman presentation for my PhD defense at University of Twente, 2011/11/30. Full text of dissertation is accessible at: http://www.itc.nl/library/papers_2011/phd/ma.pdf]]> Thu, 24 Oct 2013 15:22:59 GMT /slideshow/ontology-spectrum-for-geological-data-interoperability-phddefence/27543928 MarshallXMa@slideshare.net(MarshallXMa) Ontology spectrum for geological data interoperability (PhD defense nov 2011) MarshallXMa Ontology spectrum for geological data interoperability. A 10-minutre layman presentation for my PhD defense at University of Twente, 2011/11/30. Full text of dissertation is accessible at: http://www.itc.nl/library/papers_2011/phd/ma.pdf <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ontologyspectrumforgeologicaldatainteroperabilityphddefence-131024152259-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Ontology spectrum for geological data interoperability. A 10-minutre layman presentation for my PhD defense at University of Twente, 2011/11/30. Full text of dissertation is accessible at: http://www.itc.nl/library/papers_2011/phd/ma.pdf

Ontology spectrum for geological data interoperability (PhD defense nov 2011) from Xiaogang (Marshall) Ma

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0 A use case-driven iterative method for �building a provenance-aware GCIS ontology /slideshow/esip-s2013x-magcissessionv1/26799085 esip-s2013-xma-gcissessionv1-131002150321-phpapp01
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]]> Wed, 02 Oct 2013 15:03:21 GMT /slideshow/esip-s2013x-magcissessionv1/26799085 MarshallXMa@slideshare.net(MarshallXMa) A use case-driven iterative method for �building a provenance-aware GCIS ontology MarshallXMa <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/esip-s2013-xma-gcissessionv1-131002150321-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

A use case-driven iterative method for building a provenance-aware GCIS ontology from Xiaogang (Marshall) Ma

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0 A short introduction to GIS /slideshow/a-short-introduction-to-gis/26716356 introtogis-130930194254-phpapp02
My first ever course lecture.]]>
My first ever course lecture.]]> Mon, 30 Sep 2013 19:42:54 GMT /slideshow/a-short-introduction-to-gis/26716356 MarshallXMa@slideshare.net(MarshallXMa) A short introduction to GIS MarshallXMa My first ever course lecture. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtogis-130930194254-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> My first ever course lecture.

A short introduction to GIS from Xiaogang (Marshall) Ma

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0 A short story of geologic time ontologies and vocabularies /slideshow/a-short-story-a/26716085 20130501esciencexma-130930192712-phpapp02
–Recent progress on geologic time ontologies and vocabularies; –Their applications; –Further works; –Recommendations for other geoscience ontology and vocabulary works.]]>
–Recent progress on geologic time ontologies and vocabularies; –Their applications; –Further works; –Recommendations for other geoscience ontology and vocabulary works.]]> Mon, 30 Sep 2013 19:27:12 GMT /slideshow/a-short-story-a/26716085 MarshallXMa@slideshare.net(MarshallXMa) A short story of geologic time ontologies and vocabularies MarshallXMa –Recent progress on geologic time ontologies and vocabularies; –Their applications; –Further works; –Recommendations for other geoscience ontology and vocabulary works. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20130501esciencexma-130930192712-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> –Recent progress on geologic time ontologies and vocabularies; –Their applications; –Further works; –Recommendations for other geoscience ontology and vocabulary works.

A short story of geologic time ontologies and vocabularies from Xiaogang (Marshall) Ma

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0 Exploratory visualization of earth science data in a Semantic Web context /slideshow/agu2012xma/15544181 agu2012xma-121207235253-phpapp01
Xiaogang Ma; Peter A. Fox - Exploratory visualization of earth science data in a Semantic Web context - Presentation IN53D-07 at AGU Fall Meeting 2012]]>
Xiaogang Ma; Peter A. Fox - Exploratory visualization of earth science data in a Semantic Web context - Presentation IN53D-07 at AGU Fall Meeting 2012]]> Fri, 07 Dec 2012 23:52:53 GMT /slideshow/agu2012xma/15544181 MarshallXMa@slideshare.net(MarshallXMa) Exploratory visualization of earth science data in a Semantic Web context MarshallXMa Xiaogang Ma; Peter A. Fox - Exploratory visualization of earth science data in a Semantic Web context - Presentation IN53D-07 at AGU Fall Meeting 2012 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/agu2012xma-121207235253-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Xiaogang Ma; Peter A. Fox - Exploratory visualization of earth science data in a Semantic Web context - Presentation IN53D-07 at AGU Fall Meeting 2012

Exploratory visualization of earth science data in a Semantic Web context from Xiaogang (Marshall) Ma

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0 https://cdn.slidesharecdn.com/profile-photo-MarshallXMa-48x48.jpg?cb=1607904510 homepages.rpi.edu/~max7/ https://cdn.slidesharecdn.com/ss_thumbnails/2015diversitydco-151019204209-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/from-data-portal-to-knowledge-portal-leveraging-semantic-technologies-to-support-interdisciplinary-studies/54138102 From data portal to kn... https://cdn.slidesharecdn.com/ss_thumbnails/20150319mcgill-v2-150404110309-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/exploring-the-web-of-data-forearth-and-environmental-sciences/46640193 Exploring the Web of D... https://cdn.slidesharecdn.com/ss_thumbnails/20150308rda-p5adoptiondco-v1-150309152738-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/20150308-rda-p5adoptiondcov1/45626537 Adoption of RDA DTR an...