The journey so far
DigiClerk (DC) has moved from a self built prototype, sitting on an offline relational database, to a minimal viable product (MVP) operating on a Mongo DB database saving to AWS. We are in Phase 3b of development and, at the end of this rollout subscribers will be able to to sign up and start using the platform. This enables us to onboard enthusiastic first adopters (pioneers) and initiate a Kickstarter campaign. Everything to date has been developed by us through elbow grease and self funding. We are now looking for Founder Members to help us make the next major leap to become a global platform. DC seeks pioneers who, for a very small sum, get life membership and the ability to influence development of the platform to better suit their interests.
Phase 3b does the following: allows Founder Members to purchase lifetime membership; sets up a recurring payment system for following Members; adds the payment step and enables payments to be accepted via Stripe; allow system admins to edit products; ensures that Members have access to the right areas based on their status; convert records that used manual PDLs referenced in the last SoW; enable test/ production mode in the app; and enable the share my records function – FaceBook/ Instagram/ Twitter/ Email/ WhatsApp.
The development road map
As soon as 3b is complete DC will work on the displaying of the records in each collection. The means that, in the People Collection, records will be displayed as: an event (and everyone related to that event); timeline of a person’s life (with events on that timeline); geographical locations of a person’s life (with events on that timeline); and a family tree. The Stamps Collection and Yachting Collections visualisations are being designed as we write. The roadmap below shows the journey and where we are. Further ahead are the other planned capabilities and technologies that the life subscriptions from Founder Members will help form and fund:
Graph database
DC sees the use of graph database technology as key to the the delivery of a unique and great service. Sitting above the Mongo DB database the graph database (most likely Neo4J) will start making the connections between records, inside and outside of DC, and offering them to DC Members.
Chatbot
Allow DC Members to type or talk to DC and ask questions to find and identify records. We have identified a suitable 3rd party provider that could be plugged into the platform. We want to make the data very accessible. Our ultimate goal is to allow users to interrogate DC on the go.
Gamification
DC wants the platform to give value to the Members and therefore ‘gamification’ will be developed. Records will be rated through quality assurance (see next paragraph). Members will be rated on their use of the platform, the quality of their records, the quality of their feedback, their use of the DC platform.. .
Quality Assurance
The great IT saying of ‘rubbish in = rubbish out’ is very relevant to DC and we don’t want that. Hence DC will implement a QA system based on objective and subjective criteria of uploaded and viewed records. DC gives every record a ‘base value’ which can only be increased by, for example, if there is an image increases the provenance of the record and therefore increases the ‘value’. If the image is crisp and clear the same applies and so on. Also whether a record is viewed or liked or stored in a Members folder or downloaded will increase the value of the record. This will allow multiple versions of the same record to appear on the platform but, as the better ones get higher values only the cream of the crop will remain visible on the platform for Members. This i(QA) nformation will also drive the gamification element to rank Members.
Revenue Credit and Electronic Wallets
General. Members will have electronic wallets into which their share of monthly subscriptions will be deposited. Eventually these will lead to the DC platform enabling trading within the Collections and most likely starting with the Stamp Collection.
Machine Learning (ML) and Artificial Intelligence (AI)
It is not easy to unravel where ML stops and AI starts so we, in DC, have combined the two into the same discussion. Firstly we see DC enhancing the uploading process by auto populating fields based on one or two initial steps by the subscriber uploading a record. We see these technologies allowing DC identify, categorise and sort stamps in the Stamp Collection or perhaps boats within the Yachting Collection…..more to follow
Application Programming Interface (API)
We see API allowing DC to reach into other datasets to find records as well as permitted sites to reach into DC records.
Facial recognition (FR)
There are many facial recognition applications out there. We want to apply FR to photos on records to try and match up with others and pull record collections together.
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