Perancangan sistem unggah mandiri repository universitas pendidikan indonesia sebagai upaya meningkatkan scholarly communication dalam era big data - Santi Santika (Jurnal Pustakawan Indonesia, 2019)
Institutional repositories at universities in Indonesia are now an important part because they are media that can facilitate the process of scholarly communication and knowledge management. In the era of big data, digital data in the Institution Repository is demanded to be able to grow quickly, large, diverse, valid, and can provide added value to the scholarly communication process. Referring to this background, this study tries to design an self-archiving system on the UPI Repository which is expected to facilitate concepts in big data and improve the process of scholarly communication process. The stages of designing an self-archiving system The UPI Repository includes analysis of system requirements in accordance with scholarly communication and the concept of big data, making the flow of designing features and menus in accordance with the results of the system analysis, designing standards related to the independent upload system, designing the procedures of the self-arching system, and designing the system interface. The UPI self-arciving System (SUMa) UPI repository can be an alternative problem solving uploading process that is owned by the UPI Library to facilitate scholarly communication. Digital data of student final assignments can be published more quickly. With fast digital data uploaded, the volume of data in the UPI Repository indirectly becomes large. This is in harmony and accommodates the character of big data high volume and velocity. Variety and veracity characters are also accommodated by the UPI SUMa Repository with review and edit features. With this feature, the UPI Library DAM Team ensures and validates data published according to standards and has been approved by the supervisor. The value function is processing digital data that has been uploaded via the SUMa UPI Repository. This value function is accommodated by the statistical report feature and keyword mapping.