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Figshare provides advice on writing data management plans as well as sharing outputs funded by NSF and NIH. Organizing outputs You probably have a variety of outputs to share. Think carefully about how they might be reused in the future and how others will need to cite your outputs. In ...
Responses return the most readily available version of the data available on any node, which might not be the latest. Writes might take some time to propagate when the partition is resolved. AP is a good choice if the business needs to allow foreventual consistencyor when the system needs t...
The issue here is that longitudinal designs require a lot of time to collect thedata, especially when the data is collected by the researcher and his team. Another possibility is that journals ask the researcher to prove the effect by replicating their own studies, whichconsumes more time and ...
Database schema Translating a hashed url to the full url Database lookup API and object-oriented design Step 4: Scale the design Identify and address bottlenecks, given the constraints. For example, do you need the following to address scalability issues?
8. Add Funding information related to your data. When typing in your funder information, Figshare will search the Dimensions database for your funder and hyperlink to the Dimensions page bridging the connection between your research outputs and the funder. To add funding information that doesn’...
Open Data Commons Attribution License (ODC-By) v1.0 With the ODC-BY 1.0 license you are free: To Share: To copy, distribute and use the database. To Create: To produce works from the database. To Adapt: To modify, transform and build upon the database. (Note: “Database...
This approach is seen in file systems and RDBMSes. Strong consistency works well in systems that need transactions. Source(s) and further reading Transactions across data centers Availability patterns There are two complementary patterns to support high availability:fail-overandreplication. ...
How much data do we expect to handle? How many requests per second do we expect? What is the expected read to write ratio? Step 2: Create a high level design Outline a high level design with all important components. Sketch the main components and connections ...
Database schema Translating a hashed url to the full url Database lookup API and object-oriented design Step 4: Scale the design Identify and address bottlenecks, given the constraints. For example, do you need the following to address scalability issues?