By Tanmaya Gupta
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Extra resources for ABAP Data Dictionary
2011) as it allows the identification, retrieval, replication, and verification of data underlying published studies, even though there are no standard formats to cite data as yet. Standardized forms of data citation could be of the utmost importance as they provide a motivation for researchers to share and publish their data, by the potential of becoming a tool of reward and acknowledgment for them (Mooney & Newton, 2012). As data citation is closely associated with data sharing, there is a need for the recognition of data as a significant contribution to the scholarly record.
In order to overcome them, we have to: 1. Discover if a suitable dataset exists. 2. Identify its location. 3. Examine the copy to see if it has deteriorated too much and/or is too obsolete to be usable or not. 4. Clarify whether it is permissible to use. 5. , if it is standardized enough to be usable with acceptable effort. 6. Judge if its description is clear enough to indicate what the given dataset represents. 7. Ascertain trust. 8. Decide if it is usable for someone’s purpose. , the existence of any of these barriers may prevent the use of the data (Buckland, 2011).
It is also related to cognitive authority, about which we will present details in the section that describes digital literacy as one of the literacies closely related to and supplementing information literacy. The next factor of data quality is authenticity, which measures the extent to which the data are judged to represent the proper ways of conducting scientific research, including the reliability of the instruments used to gather the data, the soundness of underlying theoretical frameworks, and the completeness, accuracy, and validity of the data.