AEGIS High Level Scenarios – Scenario #5 – Open Innovation platform for Data Experimentation and Service Offering

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This is the fifth and final blog post out of the 5 blog posts that will provide a view of the 5 AEGIS high level scenarios.

To find more about the AEGIS scenarios, you can visit the first blog post of this series.


Scenario 5: Open Innovation platform for Data Experimentation and Service Offering

For our final post in this AEGIS scenarios blogpost series, we have a somewhat different actor, a data analyst. Although not directly linked to a specific PSPS domain, data analysts are among our key targeted users, so the aim in this last scenario is to envision how AEGIS will help them be more productive and focus on the important parts of their work.


The background Vicente is a data analyst that has recently completed his postgraduate studies in data science and is working as an independent contractor/consultant in different firms and organisations. He is an open source and open data enthusiast and highly believes in the data sharing economy, trying to contribute back to all communities he is engaged in. His business and research interests focus on big data and data analytics technologies. He usually works from home to deliver various reports to the companies he has contracts with.
The driving need Growth of business seems to be in a good track, but Vicente is struggling with the increasing demand for data processing infrastructure he needs. It is not only his client base that is growing, but also the volume and variety of data itself are growing as well. For this reason, he has recently conducted an analysis of available solutions that could meet his needs for both experimentation and production purposes, and at the moment he has concluded that the AEGIS platform is in a position to cover his demands. What he finds especially interesting is that AEGIS inherently provides elevated support for data analytics related to public and personal safety and security applications, since he has a rich client base interested in these topics.
The core data analysis projects Vicente has already created an account in AEGIS. Since he is going to use it not only for small scale experimentation (but also for storing his data and conducting large scale analyses) he has decided to select a PAYG plan that takes into consideration the data volume retained in the platform and the computing requirements for each analysis (CPU time and Memory). Currently, he has three different repositories in his account, two that deal with data analytics services he is offering to two of his clients, and one he is using for experimentation purposes.

In the first two repositories, Vicente has set up a chain of services which conduct analyses at prescribed time intervals and deliver both data streams (via a dedicated API) and reports (through a dashboard, that is based on the default visualisation features offered by AEGIS), which are both currently set to “private”, not allowing external entities to access them. During the set-up of those repositories, Vicente has utilised the standard analytics features offered by the platform, and has built a chain of algorithms where output of one analysis if being fed into another. He has also found online in AEGIS platform some datasets which are more detailed than the ones he has used, and after a short experimentation with them in the third repository (see below), he decided that their inclusion in his business cases is quite beneficial. The first one came for free, while the second has a monthly basis usage license, which Vicente decided to acquire. However, as the data delivered by that dataset comes only in .csv format with lots of unnecessary (for Vicente) data that increase the storage needs unnecessarily, he has combined some existing AEGIS services into one larger preprocessing service that cleans the data and transforms it into JSON. Vicente has decided to make his new data manipulation service (i.e. chain of AEGIS services) available for free to everybody in AEGIS (although initially he was thinking of putting a price on it, to balance the costs he pays for the data licenses).

The playground project The third repository that Vicente has set up is his main “playground”. There he is able to upload different datasets, retrieve data from APIs, utilise the services provided by AEGIS to combine, clean and transform his own and other third-party data sources which he discovers through the platform, and is also able to conduct small scale experiments. The main objective of this is to constantly evaluate the offering of the platform (in terms of data, services and algorithms) and port artefacts that seem beneficial to his “production” repositories. For this to happen, he uses some features that allow him to replicate the attributes and environmental parameters of his “production” repositories and install them into the experimentation repository, and then try to integrate his ideas there, without compromising his running production instance.
The benefits At the end of the day, Vicente is happy for having found a platform that saves him a lot of time and of course cost for his job. Although he understands that there are some limitations in the AEGIS platform due to its nature as a centrally offered PaaS, he thinks that the trade-off of customisation for improved ease of use is completely worth it for his own case, especially since AEGIS allows him not only to “get his hands dirty” with his data more quickly, but also enables him to showcase his work to prospective collaborators or even monetise it directly.


Figure 1: Scenario in a nutshell & key benefits


Data analysts are a demanding audience to target, so the envisioned workflow is tied to a number of challenges, since AEGIS must offer an intuitive and easy to use interface but with really advanced data manipulation tasks enabled, which require strong technical support in the background in order to provide also a certain flexibility to the users, e.g. in the form of facilitating the combination and configuration of AEGIS service-chains to form integrated “user-authored” data manipulation services.

If you are eager to see how AEGIS will help bring the scenarios to life, stay tuned for our upcoming posts and remember to check our deliverables!


Blog post authors: NTUA