In view of the lack of trust mechanism in the existing multi-organization collaborative data sharing framework， the problems of data privacy and security risks， data consistency and regulatory issues regarding the usage of shared data， with the help of the properties of blockchain， a multi-organization collaborative data sharing scheme with dual authorization was proposed to solve the access problem of collaborative management of shared data between various organizational entities through dual authorization. Firstly， Attribute-Based Access Control （ABAC） technology was utilized to manage shared data using a set of attributes of different organizations to achieve the first layer of authorization and prevent unauthorized access by unauthorized users. Secondly， based on access control， a multi-signature protocol was introduced for the second layer of authorization， regulating the access to shared data of collaborative organizations， thereby enhancing access security. Experimental results show that the when the number of collaborative organizations is 4，the overall time cost of system is 21 s. When the number of collaborative organizations increases to 10， the proposed scheme can still maintain low time overhead， so the proposed scheme can meet the needs of safety and practicability in actual production at the same time.

As the radio frequency communication technology gets more mature and the hardware manufacturing cost decreases, Radio Frequency IDentification (RFID) technology has been applied in the domains of real-time object monitoring, tracing and tracking. In supply chain applications, there are usually a great number of RFID objects to be monitored and traced, and objects' locations are changed essentially, so how to query the locations and the histories of location change of the RFID objects, from the huge volume of RFID data, is an urgent problem to be addressed. Concerning the characteristics of mobile RFID objects and the tracing query requirements in supply chain applications, an effective spatio-temporal index, called as CR-L, was put forward, and its structure and maintenance algorithms, including insertion, deletion, bi-splitting, and lazy splitting, were discussed in detail. In order to support object queries effectively, a new calculation principle of Minimum Bounding Rectangle (MBR), considering the three dimensional information including readers, time and objects, was presented to cluster the trajectories by the same reader at close time into the same node or the neighboring nodes. As to trajectory queries, a linked list was designed to link all trajectories belonging to the same object. The experimental results verify that CR-L has better query efficiency and lower space utilization rate than the existing method.