Assigning Schema Labels Using Ontology And Hueristics

Bioinformatics data is growing at a phenomenal rate. Besides the exponential growth of individual databases, the number of data depositories is increasing too. Because of the complexity of the biological concepts, bioinformatics data usually has complex data structures and cannot be easily captured with relational model. As a result, various flat-file formats have been used. Although easy for human interpretation, flat-file formats lack of standards and are hard to be recognized automatically. As a result, manually written parsers are widely used to extract data from them. This has limited the readiness of the data for data consuming programs, such as integration systems. This paper presents a data mining based approach for automatically assigning schema labels to the attributes in a flat-file biological dataset. In conjunction with our prior work on semi-automatically identifying the delimiters and automatically generating parsers, automatic schema labeling offers a novel and p...

• Type: Conference
• Year: 2006
• Where: BIBE
• Authors: Xuan Zhang, Ruoming Jin, Gagan Agrawal
• Keywords: BIBE 2006, Bioinformatics, Bioinformatics Data, Biological, Data Mining