Provenance of Figures in the Global Change Information System

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Abstract:

The Draft of the 2013 National Climate Assessment (NCA), developed by the US Global Change Research Program, is a US government document which thoroughly describes the impact of climate change on the United States. It will serve as the base of the Global Change Information System (GCIS), which is a portal allowing users to interact with the NCA and to trace the provenance of figures and data sources used in the NCA using the ISO 19115: 2003 standards. The goal of provenance tracking within the GCIS is to provide information to allow a user to reproduce an image. However, the tracking of provenance is a complex task due to the vast amount of information for which metadata needs to be captured and modeled (Tilmes et al. 2013), as well as problems with the availability of data sources, especially non-archived outputs from scientific investigations which need to be tracked down individually. Here, we present a sample process of lineage tracing for a particular NCA figure lacking a complete set of metadata. The approach of lineage tracing is described here in three ways: (a) a graphical, information representation of the provenance scenario, (b) a formal provenance diagram using terminology from the W3C PROV Data Model and Ontology, and (c) a RDF description serialized in Turtle format.

History

DateCreated ByLink
July 16, 2013
17:44:06
Xiaogang MaDownload

Related Projects:

Global Change Information System: Information Model and Semantic Application Prototypes (GCIS-IMSAP)
Principal Investigator: Peter Fox
Description: The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) proposes to facilitate the vocabulary and ontology development within the context of the overall development of semantic prototypes for the National Climate Assessment (NCA) portals using a combination of environmental inter-agency collaborations in a use-case focused workshop setting, information modeling, and software developments and deployments. The prototypes are intended to provide search and browse options that inspire confidence that all relevant information has been found; data providers will be citable with detailed provenance generation. Expected deliverables are: information models, vocabulary and ontology services for vetted climate assessment settings, and search/ browse prototypes.

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience
Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: ,
Semantic eScience
Lead Professor: Peter Fox
Description:
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

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X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: , eScience