## 3 Blockchain and Tracking Technologies in the Raw Material Sector
### Considerations on the Value of the Data in a Blockchain Environment  
To assess the full value of a blockchain environment, it is important not only to analyse the technical infrastructure, but also the content that is captured or made available via this infrastructure. In this respect, two different aspects can be considered:  
First of all, the value of the individual dataset can be assessed. In this respect, the value of the data stored on or referred to in a chain of blocks is only as good as the quality, in particular the veracity of the information entered into the blockchain. This leads to the classic \"garbage in, garbage out\" dilemma of many databases, meaning that the value of the output of data equals the value of the input of data. This understanding is based on the assumption that if the data that is introduced to the blockchain is of low value, for example because it is incorrect or incomplete, then the value of the data output of this blockchain can't be higher. And the usual reflex to this dilemma is that there should be sufficient checks of the accuracy and completeness of the input already at the beginning, when or before the data is introduced to the blockchain. However, the aforementioned approach does not cover the full potential of the blockchain. Because two essential elements of a blockchain, which can have a strong impact compared to traditional databases, have to be considered sufficiently: The high degree of data immutability and transparency that a blockchain can provide (depending on the design of the architecture) can have an indirect effect on its content, too. When there is no chance that data can be changed undetected by others, then the time of the data check does not necessarily always have to be right at the beginning when the data is first recorded. Blockchain technology can therefore lead to greater flexibility in the timing of data verification. The purpose as well as the need or effort required for the validation may also play a role in this respect. If data has been manipulated after it was added to the blockchain, it can be detected by comparison with the original blockchain data. This not only increases the risk for manipulators accordingly, but also for those who may want to later claim (incorrectly) that data was manipulated by others further along the chain. Finally, immutability and transparency can enable data validation at a later point in time, highlighting when and by whom the data was first introduced into the blockchain, because since then every edit to the data is immutably tracked. All in all, the immutability and transparency of blockchain technology can generate a high degree of trust for information stored on-chain. Yet the issue of how to enter trusted data into the blockchain, leads us to consider tracking technologies in more detail. Suggested Taxonomy: Tracking Technologies to Effectively Capture and Input Key Data on the Blockchain  
Within this paper, we consider the majority of tracking technologies to be part of the IoT ecosystem and suggest a taxonomy with their key features, benefits and use cases in the mining industry. Although technologies such as markers and QR/Barcodes are not necessarily electronic devices, they can integrate with other IoT objects and provide or qualify a digital identity. The common element connecting all these technologies is that they include functionalities that can capture and communicate granular, timely, relevant and accurate data, which can be automatically or manually entered into the blockchain. We have analysed the following most common physical tracking methods which will be described and exemplified in more detail below:  
* Video monitoring (Table 1)
* Bar and QR codes (Table 2)
* Markers and taggants (Table 3)
* Cellular, near range and low power network tracking tools (Table 4)
* Satellite network tracking tools (Table 5)  
In a further step, we examined and classified the aforementioned technologies with respect to certain characteristics that are generally particularly relevant for physical tracking.