Data Provenance
In French, “provenir” means “to come from,” and the word provenance in English also originates from the same term. Data provenance methodology helps in keeping records in regards to the origins and the original creator of the data.
As we all know, for an organization, data is the most valuable asset. And data in the repository could be in any form like old or new and qualitative or quantitative, plus every day your organization’s data repository gets filled with a variety of data.
In various industries and organizations, it has been analyzed that because of bad presentation, and no information about the origins of the data source which might lead to certain losses over a period.
In almost every organization, data sets are used and reformulated or reworked to create new data.
And, I’m sure your organization is also doing the same but do you know in this process, the provenance of data is very important because it guarantees that data creators are held accountable for their research work.
This practice helps other researchers to use the information with assurance, for proper data usage.
I hope this would’ve helped you to understand about data provenance. In the next stage of this blog, we will try to understand some data provenance tools which allow you to maintain your data from its origin to its current usage.
4 Data Provenance Tools to Maintain your Database
If you are looking for a tool that is proficient in auditing and provenance specifically, then CamFlow is the tool you should go for.
In 2014, the development of CamFlow started at Cambridge University. CamFlow stands for "Cambridge information Flow architecture."
CamFlow is specifically designed for capturing data provenance. This is easy to install the tool in your business process. With these three steps, you can install CamFlow.
First, install package manager, these packages are hosted on packagecloud. Second, build the kernel on your local machine. And third, use any external tools like Citrix VM Tools or Vagrant to set up a virtual machine.
Kepler is free software with multi-role capabilities. Kepler supports scientific workflow, semantic workflow, hierarchical workflows, and sharing workflow.
And it’s even better at handling provenance. This system allows you to understand the origins of your data result and by understanding that, you can repeat your experiments.
While working on Kepler, your data will be automatically saved at short intervals (this exactly works like Google Docs).
This system also allows you to track how your data is being altered and where is it in use at the current moment.
The abbreviation of the Linux provenance module is “LPM.” LPM is usable for cyber resilience. This tool is highly capable of detecting fraud and protecting your data from any harm.
LPM system is specifically designed to provide a reference monitor in case of a data attack.
LPM is not just a provenance aware operating system but also a trusted framework which captures data provenance that can serve as an anchor for other provenance aware mechanisms as well.
LPM module is featured with a Linux kernel, which has 178 dedicated provenance collection hooks, all of these hooks are configured with provenance module, and further on, these hooks can be configured with several Netfilter hooks.
The open provenance model is featured with three tools ProvStore, Validator, and Translator.
ProvStore represents a repository that allows you to store your data, browse, and manage your provenance document via a web interface.
It also allows you to upload your data on the cloud with access features.
With their REST API feature, it gives additional security to your data. ProvStore also gives you a folder-based structure to organize your data in your way.
Visualize is another feature you get with an open provenance model. This will allow you to view your data in graphical representation.
You can also export your data in various formats like PROVN, JSON, TURTLE, and XML.
While on the other hand, the translator tool can be used for translating PROV representation to other representations like JSON, PROVX, PROVN, TURTLE, TRIG, and SVG.
Conclusion
There is no doubt that adopting data provenance in your business system will save you a ton of money and this will also give a structure to your data.
The above-mentioned data provenance tools are a few of the best options available in the market and can certainly help you understand your data better.
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