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Data scraping is most often done either to [[Interface (computing)|interface]] to a [[legacy system]], which has no other mechanism which is compatible with current [[computer hardware|hardware]], or to interface to a third-party system which does not provide a more convenient [[Application programming interface|API]]. In the second case, the operator of the third-party system will often see [[screen scraping]] as unwanted, due to reasons such as increased system [[load (computing)|load]], the loss of [[advertisement]] [[revenue]], or the loss of control of the information content.
Data scraping is generally considered an ''[[ad hoc]]'', inelegant technique, often used only as a "last resort" when no other mechanism for data interchange is available. Aside from the higher [[computer programming|programming]] and processing overhead, output displays intended for human consumption often change structure frequently. Humans can cope with this easily, but a computer program will fail. Depending on the quality and the extent of [[error handling]] logic present in the [[computer]], this failure can result in error messages, corrupted output or even [[program crash]]es.
However, setting up a data scraping pipeline nowadays is straightforward, requiring minimal programming effort to meet practical needs (especially in biomedical data integration).<ref>{{Cite journal |last=Glez-Peña |first=Daniel |date=April 30, 2013 |title=Web scraping technologies in an API world |url=https://academic.oup.com/bib/article/15/5/788/2422275 |journal=Briefings in Bioinformatics |volume=15 |issue=5 |pages=788–797}}</ref>
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