Difference between revisions of "SolutionsUseCase CoastsOcean Arctic 1a"
From Earth Science Information Partners (ESIP)
(How users seek and evaluate interdisciplinary data to address issues related to Arctic coastal erosion.) |
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===Short Definition=== | ===Short Definition=== | ||
− | + | This use case was developed during a small workshop that brought together scientists from diverse physical, biological, and social science disciplines to address how they would search for and assess interdisciplinary data to address important Arctic coastal science questions. Three facilitated groups | |
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+ | # Examine the relationship between sea ice retreat and coastal changes (exposure to storminess, wave erosion, and coastal retreat) and assess the vulnerability of coastal settlements to projected reductions in sea ice. | ||
+ | # Examine the kinetics of UV effects on photosynthesis in kelp (Laminaria saccharina and L. solidungula), which are distributed throughout the circumpolar Arctic. Use existing measurements of surface UVB and UVB penetration to arctic kelp beds to establish differences in sensitivity to UV radiation in plants exposed to different natural light environments during the nine-month ice covered period. | ||
===Purpose=== | ===Purpose=== | ||
− | + | Problem statements: | |
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+ | * It’s difficult to locate data needed to improve our understanding of Arctic coastal processes. | ||
+ | * Once data are located, lack of interoperability between distributed data streams and systems makes it difficult to acquire desired data and difficult to analyze/compare data from different data sets. | ||
===Describe a scenario of expected use=== | ===Describe a scenario of expected use=== | ||
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===Actors=== | ===Actors=== | ||
+ | * Data Creator | ||
+ | * Data Seeker | ||
+ | * Data Expert | ||
+ | * Data Visualizer | ||
+ | * Data Modeler | ||
+ | * Metadata Archiver | ||
+ | * Data Archiver: Manages both data and metadata | ||
+ | |||
+ | See also the "Stakeholders and User Types":http://ipydata.projectpath.com/W359651. | ||
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====Primary Actors==== | ====Primary Actors==== | ||
− | + | * Data Seeker | |
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===Preconditions=== | ===Preconditions=== | ||
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===Postconditions=== | ===Postconditions=== | ||
− | + | Data Seeker has data and associated metadata in preferred format and on local media. | |
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===Normal Flow (Process Model)=== | ===Normal Flow (Process Model)=== |
Revision as of 09:43, April 11, 2007
Return to: Use_Cases
Plain Language Description
Short Definition
This use case was developed during a small workshop that brought together scientists from diverse physical, biological, and social science disciplines to address how they would search for and assess interdisciplinary data to address important Arctic coastal science questions. Three facilitated groups
- Examine the relationship between sea ice retreat and coastal changes (exposure to storminess, wave erosion, and coastal retreat) and assess the vulnerability of coastal settlements to projected reductions in sea ice.
- Examine the kinetics of UV effects on photosynthesis in kelp (Laminaria saccharina and L. solidungula), which are distributed throughout the circumpolar Arctic. Use existing measurements of surface UVB and UVB penetration to arctic kelp beds to establish differences in sensitivity to UV radiation in plants exposed to different natural light environments during the nine-month ice covered period.
Purpose
Problem statements:
- It’s difficult to locate data needed to improve our understanding of Arctic coastal processes.
- Once data are located, lack of interoperability between distributed data streams and systems makes it difficult to acquire desired data and difficult to analyze/compare data from different data sets.
Describe a scenario of expected use
A verbose (more detailed) description of one instance of a problem to be solved, what resources are generally needed (if known) and what a successful outcome and impact may be. In this case, who might be expected to do the work or provide the resources and who might be expected to benefit from the work. List any performance or metric requirements for this use case and another other considerations that a user would expect.
Definition of Success
Quick test that would show whether or not the case is working as described.
Formal Use Case Description
Use Case Identification
- Use Case Designation
- <ApplicationArea>.<SubArea>.<ReferenceNumber>
- Use Case Name
- <Insert short name and long name>
Revision Information
- Prepared by:
- <Author(s) with responsibility>
- <Affiliation>
- <Date/Time created>
- Version X.N.a (can be labeled draft if X=0)
- Modified by:
- <Modifier Name/Affil>, <Date/time>, <Brief Description>
Definition
First paragraph is short description, second paragraph, etc. may contain further details.
Through this use case, the system User locates and identifies datasets (collections of related grandules) for use or processing. This process results in the User having access to a subset of the datasets in the portal that meet the requirements of the User. Individual datasets, and their constituent granules, may then be identified for further action or processing (e.g. Visualization, analysis, download).
Successful Outcomes
- 1.Operation succeeds and user obtains QQQ.
Failure Outcomes
- 1.Operation fails to return any XXX. Should instead YYYY.
- 2.Illegal input of AAA, Should instead ZZZZ
General Diagrams
Schematic of Use case
A diagram of how the different elements and people/processes may fit together in the use case (if possible do not refer to specific technologies).
Use Case Elaboration
This section is intended to be completed with the details of the use case that are required for implementation. This section is not intended to be filled in by an application user.
Actors
- Data Creator
- Data Seeker
- Data Expert
- Data Visualizer
- Data Modeler
- Metadata Archiver
- Data Archiver: Manages both data and metadata
See also the "Stakeholders and User Types":http://ipydata.projectpath.com/W359651.
Primary Actors
- Data Seeker
Preconditions
- 1.Collection metadata have been entered into the system
- 2.Collection metadata have been validated
- 3.Collection metadata have been published
Postconditions
Data Seeker has data and associated metadata in preferred format and on local media.
Normal Flow (Process Model)
- 1)The user selects the 'dataset discovery' tool collection from the user interface
- 2)The user performs a 'simple' search using a simple interface that searches commonly queries dataset attribute fields for matching text/terms.
- 3)The results of the search are presented to the user with appropriate action controls associated with the datasets.
- 4)The user selects one of the action controls to 'use' the identified dataset(s) in a specified action (i.e. Visualization, download, processing)
Alternative Flows
- 1)The user selects the 'dataset discovery' tool collection from the user interface
- 2)The user selects a control that provides access to an advanced search tool that supports spatial, temporal, and parametric search methods. Flow then extends to EIE11-EIE14.
Special Functional Requirements
None
Extension Points
- <Cluster>.<SubArea>.<number>.<letter+1> something added or a variant.
E.g. AQ.Smoke.1.b something added or a variant
- <Cluster>.<SubArea>.<number>.<letter+2> something added or a variant
- <Cluster>.<SubArea>.<number>.<letter+3> something added or a variant
Diagrams
Use Case Diagram
State Diagram
Activity Diagram
Other Diagrams
Non-Functional Requirements
Performance
Reliability
Scalability
Usability
Security
Other Non-functional Requirements
Selected Technology
Overall Technical Approach
Architecture
Technology A
Description
Benefits
Limitations
Technology B
Description
Benefits
Limitations
References
None