Abstract
The Big Data contains essential information for large organizations to provide new insight potential. Due to the new technological developments that have developed with Industry 4.0, data is produced in increasing volumes. Data Sharing Platforms are needed to cope with the volumes of this data and to transform data into valuable information. In line with this need, a document-based data-sharing platform software architecture is proposed within the scope of this research. The Data Sharing Platform Architecture we recommend; is designed for a document-based data management platform designed to process data at scale for analytical purposes. In the proposed study, Metadata management is used to prevent the large volume of data obtained from becoming complex and unusable. The proposed architecture has a metadata store with an enriched toolset to identify the data owner and store the version and lineage information. In the study, to provide easy access to the correct data, the locations of the data needed are shown to the users in detailed figures. To clean the data in the most appropriate quality, additional development studies are integrated into the system that will enable the user to pre-process the data. There is an operational security control to use the data securely. A standard user group management, which may vary according to operating systems, is integrated into the proposed software architecture. Again, the proposed software architecture categorizes the data by tagging it in stochastic data sets. It can offer suggestions in a way that can make suggestions according to the roles of the following users. In addition, a version and rule adaptation method is provided to deal with changes over time. A personalized rule customization method is proposed to meet the system's need to respond to the specific needs of each user.We present the details of the document-based data-sharing platform software architecture we are developing within the scope of this conference paper.
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