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KIT AIS Data Set Multiple labeled training and evaluation datasets of aerial images of crowds. Images manually labeled to show paths of individuals through crowds. ~ 150 Images with paths People tracking, aerial tracking 2012 [162] [163] M. Butenuth et al. Wilt Dataset Remote sensing data of diseased trees and other land cover.
Covertype Dataset Data for predicting forest cover type strictly from cartographic variables. Many geographical features given. 581,012 Text Classification 1998 [311] [312] J. Blackard et al. Abscisic Acid Signaling Network Dataset Data for a plant signaling network. Goal is to determine set of rules that governs the network. None. 300 Text
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]
Data sanitization is an integral step to privacy preserving data mining because private datasets need to be sanitized before they can be utilized by individuals or companies for analysis. The aim of privacy preserving data mining is to ensure that private information cannot be leaked or accessed by attackers and sensitive data is not traceable ...
Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Common Crawl is a nonprofit 501(c)(3) organization that crawls the web and freely provides its archives and datasets to the public. [1] [2] Common Crawl's web archive consists of petabytes of data collected since 2008. [3] It completes crawls approximately once a month. [4] Common Crawl was founded by Gil Elbaz. [5]
Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. [1]
The user, rather than the database itself, typically initiates data curation and maintains metadata. [8] According to the University of Illinois' Graduate School of Library and Information Science, "Data curation is the active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education; curation activities enable data discovery and ...