real issues...

the other background

cynefin

conway's law

organisations which design systems...are constrained to produce designs which are copies of the communication structures of these organisations

ladder of abstraction

 

the future of computing is analog

https://onezero.medium.com/the-future-of-computing-is-analog-e758471fbfe1

 

dynamicland schools

http://worrydream.com/#!2/LadderOfAbstraction

https://dynamicland.org

 

teaching robots to dance

https://medium.com/vertical-learning/teaching-a-robot-how-to-dance-78ee07ebd4a8

analog?

In general, digital computing deals with integers, binary sequences, deterministic logic, and time that is idealized into discrete increments, whereas analog computing deals with real numbers, nondeterministic logic, and continuous functions, including time as it exists as a continuum in the real world.

Many systems operate across both analog and digital regimes. A tree integrates a wide range of inputs as continuous functions, but if you cut down that tree, you find that it has been counting the years digitally all along.

analog

play, modulate, be forgiving

digital

preset

alienating, intolerant of error 

progress is a continuous function!

establishment

reference

events

establishment

reference

events

static

dynamic

can we do better?

A paradox is not a conflict within reality. It is a conflict between

reality and your feeling of what reality should be like.

     - Richard Feynman

 

You never change things by fighting the existing reality.
To change something, build a new model that makes the existing model obsolete.

R. Buckminster Fuller 

data & infrastructure

constrain the possible...

what if we

embrace the chaos

one way in

one way out

publish()

any data

automatic linking

graphQl()

automatic schema generation

graphql primer

....

an API service for data

technology / storage agnostic

successor to REST

privacy & encryption as standard

without privacy

privacy policy as data

with privacy

demo

gql

input & data

services...

alignment/classifier

lesson planner, alignment

multi-model

day-book

traversal

data as signal - load from 0

accept the dynamic

 

wellbeing

tasks

syllabus

observations

assessments

progress

 

data as signal

ephemeral processing;

play & improvise

 

establishment

reference

events

n3 deep dive

layout

individual

school

system

intra-system

N3 nodes can run as self-contained services on a single machine to allow inter-application interoperability

N3 nodes can be run at a school level to allow interoperability and aggregation of data for analytics

N3 nodes form a distributed network to allow sharing and interoperability across an enterprise 

N3 systems can communicate across organisational boundaries to share student information between organisations and systems

n3 components

n3w

publish()

query()

contexts

crdt

streaming / syncing

data-store

n3 components

 

deep6

crdt

gql

context

streaming

privacy

web

 

all deployed in single n3w binary

deep6

publish()

file, http request, stream

query()

findById()
findByValue()
findByType()
findByPredicate()
traversalWithId()
traversalWithValue()

hexastore extended with 

automated linking

https://people.csail.mit.edu/tdanford/6830papers/weiss-hexastore.pdf

Hexastore: Sextuple Indexing for Semantic Web Data Management

crdt manager

version-vector map-based

ensures causal consistency of

all updates across a distributed

network

 

http://nova-lincs.di.fct.unl.pt/system/publication_files/files/000/000/666/original/a12-van_der_linde.pdf?1483708753

https://arxiv.org/pdf/1011.5808.pdf

 ∆-CRDTs: Making δ-CRDTs Delta-Based

graphQL manager

Attaches to read stream of

crdt manager

creates gql-schema and 

therefore data access to

data objects seen by the context.

 

Adds universal query info 

object to access all

data through d6 methods.

context manager

Creates safe bounded areas for

data sharing.

Protected by symmetric keys and jwt tokens for access.

Applies privacy per context.

Passes data through

CRDT-layer and into

streaming engine.

Reads data from streaming layer, via CRDT into context data-store (deep6)

streaming

NATS 2.0

high-performance

clustering/syncing/scalability

distributed authn/authz

 

 

https://nats.io

privacy

Enforces POD/PPOD

data policy controls.

Data can be redacted/replaced

dynamically or 

permanently

 

n3w web-server

the single user binary

that wraps the whole lot

together

 

createContext()

publish()

query()

 

15Mb

20Mb in use

high performance

 

implications

infrastructure for an analog future

rethink how we make software

 

benefit from well-managed standardised data, but accept the chaos of schools

 

progress is a signal not a state