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Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability. The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research.
A transparency report is a statement issued semesterly or annually by a company or government, which discloses a variety of statistics related to requests for user data, records, or content. Transparency reports generally disclose how frequently and under what authority governments have requested or demanded data or records over a certain ...
Scholarly research in any academic discipline may also be labeled as (partly) transparent (or open research) if some or all relevant aspects of the research are open in the sense of open source, [20] open access and open data, [21] thereby facilitating social recognition and accountability of the scholars who did the research and replication by ...
The Data Project used rankings from Open Data Watch to explore how the U.S. compares to other countries in data transparency and openness.
Network transparency refers to the ability of a protocol to transmit data over the network in a manner which is not observable to those using the applications that are using the protocol. In this way, users of a particular application may access remote resources in the same manner in which they would access their own local resources.
In data compression and psychoacoustics, transparency is the result of lossy data compression accurate enough that the compressed result is perceptually indistinguishable from the uncompressed input, i.e. perceptually lossless. A transparency threshold is a given value at which transparency is reached. It is commonly used to describe compressed ...
Data independence is the type of data transparency that matters for a centralized DBMS. [1] It refers to the immunity of user applications to changes made in the definition and organization of data. Application programs should not, ideally, be exposed to details of data representation and storage.
Data sharing is the practice of making data used for scholarly research available to other investigators. Many funding agencies, institutions, and publication venues have policies regarding data sharing because transparency and openness are considered by many to be part of the scientific method. [1]