Anonymizing relational and textual data

A computer program product for anonymizing data, the computer program product comprising:

• one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising:
• program instructions to receive a mixed-type dataset with at least two relational attributes and at least one textual attribute;
• program instructions to running, by one or more processors, the mixed-type dataset through a text annotator to discover a set of personally identifiable information (PII);
• program instructions to create a set of ghost attributes to add to the mixed-type dataset, wherein each ghost attribute of the set of ghost attributes corresponds to a PII of the set of PII discovered by the text annotator;
• program instructions to anonymize data of the at least two relational attributes and the set of ghost attributes;
• program instructions to replace each PII of the set of PII in the textual attribute with the corresponding anonymized data in the at least two relational attributes or the set of ghost attributes to create an anonymized mixed-type dataset;
• program instructions to remove the set of ghost attributes from the anonymized mixed-type dataset;
• program instructions to shuffle records of the anonymized mixed-type dataset based on equivalence classes to create a shuffled anonymized mixed-type dataset;
• and
• program instructions to output the shuffled anonymized mixed-type dataset.

A computer system for anonymizing data, the computer system comprising:

• one or more computer processors;
• one or more computer readable storage media;
• program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising:
• program instructions to receive a mixed-type dataset with at least two relational attributes and at least one textual attribute;
• program instructions to running, by one or more processors, the mixed-type dataset through a text annotator to discover a set of personally identifiable information (PII);
• program instructions to create a set of ghost attributes to add to the mixed-type dataset, wherein each ghost attribute of the set of ghost attributes corresponds to a PII of the set of PII discovered by the text annotator;
• program instructions to anonymize data of the at least two relational attributes and the set of ghost attributes;
• program instructions to replace each PII of the set of PII in the textual attribute with the corresponding anonymized data in the at least two relational attributes or the set of ghost attributes to create an anonymized mixed-type dataset;
• program instructions to remove the set of ghost attributes from the anonymized mixed-type dataset;
• program instructions to shuffle records of the anonymized mixed-type dataset based on equivalence classes to create a shuffled anonymized mixed-type dataset;
• and
• program instructions to output the shuffled anonymized mixed-type dataset.