@article{3172,
  author = {Mammadov Hasan, Yan Li, Muhammad Waqas Ahmad},
  title = {TSV2RDF: Generating RDF Data Model from TSV File Format Using Semantic Web Technologies},
  journal = {Journal of Digital Information Management},
  year = {2021},
  volume = {19},
  number = {1},
  doi = {https://doi.org/10.6025/jdim/2021/19/1/10-26},
  url = {https://www.dline.info/fpaper/jdim/v19i1/jdimv19i1_2.pdf},
  abstract = {The Semantic Web empowers machines to better understand the information by associating precise
meanings with the data. Resource Description Framework (RDF) lies among basic building blocks for the Semantic Web, to give formal definitions to the data. However humongous amount of majority governments and official data exist in various legacy file formats, generally in the tabular form such as tab-separated values (TSV) or relational databases. Nevertheless, there
existed no built-in or standardized implementation to convert TSV to RDF using Semantic Web technologies. This paper focused on deliberation to define and implement a novel mechanism for data conversion. The proposed technique involved in conversion of TSV data to RDF format based on RDF Mapping Language (RML)with direct mapping technique. RML is the RDF mapping language, which is meant to define mapping functions from heterogeneous file formats to RDF data structure. In this paper, an RML and direct mapping based RDF generation software TSV2RDF has been created. TSV2RDF has been evaluated at various benchmark TSV datasets. The proposed conversion method has produced comparative results with increased accuracy and reduced processing time. The performance of developed software exhibits significant performance 
compared with other datasets. Significant usability at TSV to RDF transformation is suggested by smart adoption of the TSV2RDF. },
}