The elf Inandu returned all excited to the castle. He had found a data chest with a correct label with the correct location of where he later found the chest. This chest contained a magic spell of how to turn water into gold.
The überwizard Ikloton opened the data chest and started reading through the spell.
– “This is good”, he rejoiced. “Really, really good. Inandu, I think this is the end of our quest.”
– “Should I call upon the prince?” the elf asked, blushing with pride that he had brought this chest to the castle.
– “Yes … But wait!” the überwizard grunted, first turning white, then red with anger: “In step 4 of the spell, the wizard authors refer to a procedure they have used to conjure the key ingredient used in this spell – violet lizards with green dots. What is this procedure called? And how can it be found?” The spell gave no indication of this, neither did the data chest or its label. Thus, even though the data chest contained the right spell, it was useless to the data wizards at the castle.
– “I’m … so … sorry”, mumbled the elf, his eyes brimming with tears. He felt like crying for days, which he actually could.
– “Me too”, said Ikloton. “So close, and yet we are nowhere”.
It is important to be able to trace the connections between your data set and data sets that are related to it. This can be done by linking to other data sets that are not included in your work. It can also be done through connections that show how your data set is derived from a previous version or e.g. is processed data based on some raw data. Either way, it is important to maintain these connections by referencing between data sets. If your data set relies on other’s data – or your own – this is also an appropriate method to ensure that proper credit is given to the people who created the data that your data is based upon.