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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Collaboratory | 4/6 | https://en.wikipedia.org/wiki/Collaboratory | reference | science, encyclopedia | 2026-05-05T09:03:22.295395+00:00 | kb-cron |
BSC also provides a data provenance tool and a data organization tool. These tools allow a hierarchical tree to display the historical lineage of a data set. From this tree-view the scientist may select a particular node (or an entire branch) to access a specific version of the data set (Chin & Lansing, 2004). The task management provided by BSC allows users to define and track tasks related to a specific experiment or project. Tasks can have deadlines assigned, levels of priority, and dependencies. Tasks can also be queried and various reports produced. Related to task management, BSC provides workflow management to capture, manage, and supply standard paths of analyses. The scientific workflow may be viewed as process templates that captures and semi-automate the steps of an analysis process and its encompassing data sets and tools (Chin & Lansing, 2004). BSC provides project collaboration by allowing scientists to define and manage members of their group. Security and authentication mechanisms are therefore applied to limit access to project data and applications. Monitoring capability allows for members to identify other members that are online working on the project (Chin & Lansing, 2004). BSC offers community collaboration capabilities: scientists may publish their data sets to a larger community through the data portal. Notifications are in place for scientists interested in a particular set of data - when that data changes, the scientists get notification via email (Chin & Lansing, 2004).
=== Diesel Combustion Collaboratory === Pancerella, Rahn, and Yang (1999) analyzed the Diesel Combustion Collaboratory (DCC) which was a problem-solving environment for combustion research. The main goal of DCC was to make the information exchange for the combustion researchers more efficient. Researchers would collaborate over the Internet using various DCC tools. These tools included “a distributed execution management system for running combustion models on widely distributed computers (distributed computing), including supercomputers; web accessible data archiving capabilities for sharing graphical experimental or modeling data; electronic notebooks and shared workspaces for facilitating collaboration; visualization of combustion data; and videoconferencing and data conferencing among researchers at remote sites” (Pancerella, Rahn, & Yang, 1999, p. 1). The collaboratory design team defined the requirements to be (Pancerella, Rahn, & Yang, 1999):
Ability share graphical data easily; Ability to discuss modeling strategies and exchange model descriptions; Archiving collaborative information; Ability to run combustion models at widely separated locations; Ability to analyze experimental data and modeling results in a web-accessible format; Videoconference and group meetings capabilities. Each of these requirements had to be done securely and efficiently across the Internet. Resources availability was a major concern because many of the chemistry simulations could run for hours or even days on high-end workstations and produce Kilobytes to Megabytes of data sets. These data sets had to be visualized using simultaneous 2-D plots of multiple variables (Pancerella, Rahn, & Yang, 1999). The deployment of the DCC was done in a phased approach. The first phase was based on iterative development, testing, and deployment of individual collaboratory tools. Once collaboratory team members had adequately tested each new tool, it was deployed to combustion researchers. The deployment of the infrastructure (videoconferencing tools, multicast routing capabilities, and data archives) was done in parallel (Pancerella, Rahn, & Yang, 1999). The next phase was to implement full security in the collaboratory. The primary focus was on two-way synchronous and multi-way asynchronous collaborations (Pancerella, Rahn, & Yang, 1999). The challenge was to balance the increased access to data that was needed with the security requirements. The final phase was the broadening of the target research to multiple projects including a broader range of collaborators. The collaboratory team found that the highest impact was perceived by the geographically separated scientists that truly depended on each other to achieve their goals. One of the team's major challenges was to overcome the technological and social barriers in order to meet all of the objectives (Pancerella, Rahn, & Yang, 1999). User openness and low maintenance security collaboratories are hard to achieve, therefore user feedback and evaluation are constantly required.
=== Other collaboratories === Other collaboratories that have been implemented and can be further investigated are: