Finding a "ToolMatch" for your Data Collection

Printer-friendly version


This breakout session will briefly describe the initial use cases, conceptual model, and assumptions underlying the ToolMatch service being built by Semantic Web Cluster participants in collaboration with the ESIP Energy & Climate Cluster, and the ESIP Products & Services Committee using Semantic Web technologies. The initial phase of the ToolMatch service will be demonstrated from both the tool developer and the data collection user perspectives. Following the demonstration, workshop participants will be asked to input specific information about visualization tools appropriate for Earth Science-focused data collections, and / or specific information about data collections appropriate for the use of Earth Science-appropriate visualization tools. Subsequent successes and failures of the service will be discussed among the ToolMatch development team and workshop participants for purposes of refining the use cases, clarifying assumptions and improving the ToolMatch service.


DateCreated ByLink
July 5, 2014
Patrick WestDownload

Related Projects:

TW LogoToolMatch (ToolMatch)
Description: or a given dataset, it is difficult to find the tools that can be used to work with the dataset. In many cases, the information that Tool A works with Dataset B is somewhere on the Web, but not in a readily identifiable or discoverable form. In other cases, particularly more generalized tools, the information does not exist at all, until somebody tries to use the tool on a given dataset. Thus, the simplest, most prevalent use case is for a user to search for the tools that can be used with a given dataset. A further refinement would be to specify what the tool can do with the dataset, e.g., read, visualize, map, analyze, reformat.

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
Semantic eScience
Lead Professor: Peter Fox
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.

Concepts: eScience
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