One major issue with data science results is the truthfulness of data - also known as "data veracity". In the past few years - especially last year (2014) - we have seen a rapid rise in the amount of false data creation.
Data veracity is defined as false or inaccurate data. The data may be intentionally, negligently or mistakenly falsified. Data veracity may be distinguished from data quality, usually defined as reliability and application efficiency of data, and sometimes used to describe incomplete, uncertain or imprecise data.