Matt Shearer

Domain-driven design, or domain modelling is about optimising a team's knowledge and understanding of the domain it works in. Find out how DDD can benefit your project here.

What is Domain Driven Design and why do you need it?

What is Domain-Driven Design?
Domain-Driven Design (DDD) is a method for developing a team's understanding of
a problem space. It emphasises placing the primary focus of a project on the
core area of the business (the core domain). This often takes the form of
facilitated workshops with domain experts and the development of a shared set of
conceptual models. DDD has the additional benefit of creating a shared
understanding (ubiquitous language) between teams when designing technical
solutions.

Skilled facilitation of domain modelling sessions helps our clients get to grips
with their domain. Through collaborative domain modelling exercises, we work
with stakeholders to gain a broad understanding of the target domain. We
typically focus on the high value elements of the domain, iteratively refining
and validating models to achieve the right level of detail to deliver the most
business value.

Would my project benefit from Domain-Driven design?
Common reasons that you would look to Domain Driven development would be
projects that need to distill the knowledge of domain experts into a product.
These types of projects can often suffer from a disconnect in domain
understanding. Discovering this disconnect in code or in data models is
expensive to fix. DDD can address this by tackling differences in domain
understanding before implementation begins. It can create a perfect bridge of
understanding between the business stakeholders, the problem-space, and the
technical teams.

Another application of DDD is in projects that require strong information
architecture. Where the intention is to organise a product around the entities
and relationships of the domain. This is often seen in approaches that build on
taxonomies or knowledge graphs.

We see Domain-Driven Design as a critical starting point for all our knowledge
graph implementations, and on the majority of our project engagements, including
development of our own products.

Domain-Driven Design

Data Moments enhances videos with structured data that creates new brand activation, new brand engagement, and new shoppable moments opportunities.

Data Moments - The video moment product that activates your video

Since our inception in 2014 we have been working on innovation around video
metadata technology, and Data Moments
[https://datalanguage.com/products/datamoments] is the productized upshot of all
this work. Data Moments [https://datalanguage.com/products/datamoments] 
massively boosts video reach, engagement, and monetisation opportunities.

Data Moments [https://datalanguage.com/products/datamoments] enhances video with
machine-friendly structured metadata that enables all players in the video value
chain to create new brand experiences, and to harness this new core business
data.

Data Moments on Jamie Oliver Video: HowTo Moments and Shoppable Moments
We have been working with Jamie Oliver to make the moments in his video more
"Cook along"-able, and to add products to key video moments to create "Shoppable
moments".

Screen grab showing how Data Moments
[https://datalanguage.com/products/datamoments] promotes a "shoppable moment"
when consumer intent is at its height. These Jamie Oliver Shoppable Moments
created CTR of 5.4% and ecommerce conversion of 9.6%Data Moments
[https://datalanguage.com/products/datamoments] on the Rugby World Cup: Sport
Event Moments
We worked with the Japanese broadcaster J SPORTS to enhance their Rugby World
Cup video [https://video.jsports.co.jp/] with activated video moments, promoting
their e-commerce products, their SVOD service, and highlighting each important
sporting event.

Rugby World Cup moments with new SEO and Social optimisation from Data Moments
[https://datalanguage.com/products/datamoments]. Each sporting event was
labelled with optimised metadata.

News, features and updates about our video moment product Data Moments. Find out how this innovative product harnesses structured data in video. Brought to you from the team that was foundational in the earliest large scale linked data projects in the UK.

Read news, features and updates about our video moment product Data Moments. Find out how this innovative product harnesses structured data in video.

Data Moments - News and Video Product Updates

Data Moments

Data Moments - Get the latest on this Video Data Moment Product

Data Moments: Video Moment Technology

Paul Wilton

We are trusted experts with decades of experience in delivering knowledge graph technology to global organisations. Get in touch and let's talk data.

Global Knowledge Graph Engineering by Data Language

Data Language has exceptional experience in the design, implementation and
deployment of knowledge graphs, linked data, and semantic web technologies. We
have been working with graph databases since our inception, when our founders
worked on possibly the UK’s first enterprise scale knowledge graph for BBC News
and Sport. Since then we have helped global organisations such as Cochrane,
Wellcome, and Euromoney implement them too. Our typical approach to implementing
a knowledge graph solution is:

Domain Driven Design
Through collaborative domain modelling exercises, we work with stakeholders to
gain a broad understanding of the target domain, iteratively refining and
validating ontology models to achieve the ideal level of detail to deliver the
best outcomes, business value and utility.

Technical and Data Architecture
Not all graph databases are equal. We are wholly vendor-agnostic, and our deep
experience in designing scalable, maintainable, and evolvable knowledge graph
solutions, means we will always select the right graph technology to deliver
your use-cases. We understand the difference between label-property graphs and
RDF based graph databases. We have a total grasp on the practical and pragmatic
use of semantics and inference to ensure your solution is not over-engineered
but delivers just the right level of complexity to optimise your total cost of
ownership, and ensure your solution can evolve as your business evolves.

Integration - Data and Software Engineering
We can help you integrate the knowledge graph with your business systems and
workflows, either by helping your own software engineering team with querying
the graph using query languages such as SPARQL or Gremlin, through to developing
microservices and web interfaces that encapsulate your target use-cases. We are
skilled at data engineering, and can help you populate your knowledge graph,
transforming and loading your own business data, and linking to or ingesting
open-data as required.

Automation and Deployment
We can work with and guide your own infrastructure team, or take on the task of
engineering, integration and deployment entirely ourselves. We are skilled at
contemporary best practices for deployment of infrastructure in the cloud or
on-prem. Our devops engineers are skilled in the use of infrastructure-as-code
for fully automating the deployment and maintenance of the entire knowledge
graph solution.

Graph databases

Knowledge Graph Engineering

Alexi Buckingham

Our Text AI Services are easy-to-integrate SaaS tools that use AI and machine learning to make document classification as efficient as possible. 

Document Classification Text AI Service by Data Language

AI Document Classification
Data Language has been tackling the problem of document classification for many
years and has used their wealth of experience in NLP, data science, and text
analytics to create a product that is world leading. 

Our Text AI Services are easy-to-integrate SaaS tools that use AI and machine
learning to make content categorisation and tagging as easy and efficient as
possible. Our Text AI Services dramatically reduce the cost and effort
associated with tagging and organising written content, speeding up
behind-the-scenes processes and ensuring accuracy.

With our Document Classification Text AI Service, the difficult engineering and
scaling is done for you, dramatically reducing the total cost of ownership of
developing AI based classification in-house.

Document Classification Text AI Service main features
 * Fully managed Software as a Service, trivial to integrate into your systems
 * Language agnostic
 * Classifies content using your own vocabularies and dictionaries
 * Self optimizes and learns on-the-fly independently to your workflow
 * Dramatically reduces the time, cost and complexity of tagging content
 * Gives you more time to do what you do best

Benchmarking
We have benchmarked our Document Classification Text AI Service against Reuters 
RCV1 and Arvix Academic Paper Dataset AAPD and achieved impressive results.
 Read more about the benchmarks here
[https://datalanguage.com/blog/benchmarking-tagmatic].

Our Document Classification Text AI Service is perfect for almost any text
classification problem, and in any language, some of its primary use-cases are : 

Publishing
Our Document Classification Text AI Service was originally built to tackle the 
challenges that publishers [https://datalanguage.com/tagmatic-for-publishers] 
and media organisations have with automatic and human-assisted content tagging:
reacting to new terms (tags) fast as they break in news, automatic on-the-fly
training, consistency, disambiguation, editorial tagging style  - all this is
handled out of the box by our service. 

Law and Legal Tech
Our Document Classification Text AI Service is perfect for classifying legal
texts and documents, or part-of-documents such as contract clauses. Once
trained, it can be used to automate the tagging of incoming legal documents, as
well as archives of existing documents. We have demonstrated Document
Classification Text AI Service on Hansard of some 200,000 parliamentary
interventions for the 2005/6 period , classified with >7200 categories from the
parliamentary library classification vocabulary, and achieved extremely accurate
results.

Healthcare and Life Sciences
Through our work with Cochrane, we have extensive experience with bioinformatics
vocabularies such as SNOMED-CT, MESH, and MedDRA. Our Document Classification
Text AI Service is ideally suited for the automated classification and tagging
of content against these vocabularies, whether for classifying clinical trials,
 patient records, or general medical documents.

Free Trial
If you are a publisher or work with high volumes, or large content archives and
are working on or thinking of building your own automated tagging platform, then
our Document Classification Text AI Service is an ideal solution - you can be up
and running in hours, and reduce your total cost of ownership of building,
scaling, and hosting your own AI / NLP based classification solution
dramatically. 

Please get in touch for a free trial.

News and product updates about our Text AI Services. Read about how our Text AI products are being used in innovation projects, and by our clients.

Read the latest on our Text AI Services. Projects, Innovation initiatives, and new developments for AI features in specialized use cases.

News and Product Updates about our Text AI Services

Text AI Services

AI Document Classification with Data Language Text AI Services

Tolga Ergin

It’s what we do
Building innovative data driven platforms and products is what we do. We are
experts in innovative data driven products and platforms. 

We are world class data and software engineers, and build practical machine
learning and AI solutions that deliver real business value rapidly.

But we don’t just stop at the platform, our talented developers also build
beautiful, accessible data visualisations and user experiences.

How do we do it
Our approach is multi-fold. Tried and tested, and focussed on delivering early
value.

Domain-Driven Design
To build a great product it is critical to understand the domain. We use 
domain-driven design [https://datalanguage.com/domain-driven-design] at the
outset to gain a broad-enough and deep-enough understanding of the problem space
and value-proposition not just to deliver the right solution, but to deliver the
right value too.

Minimum Useful Product
Delivering early value is key. Working with stakeholders and the outputs of
domain-modelling we identify a Minimum Useful Product (MUP), that is both
desirable and viable.

Technical Strategy
We take a practical and pragmatic approach to technical strategy
[https://datalanguage.com/technical-strategy], tailored on business vision,
rigorous risk management, lean processes for agile governance, ultimately
designing technical solutions to support market opportunities.

Iterative Full-Stack Implementation
We build a feature-driven vertical slice through our platform as early as
possible. We automate from the outset using contemporary tooling for continuous
delivery, including infrastructure-as-code, and
test/behavioural-driven-development patterns.
Our data models are maintained and evolved iteratively too, modelling
just-enough to deliver the detail of the evolving-features, while keeping in
mind the big picture domain model. 
By delivering an early vertical-slice, we identify risks and challenges early.
Our vertical-slice is iteratively evolved feature-by-feature to deliver the MUP,
with user and stakeholder feedback at each iteration.

Data Driven Product Innovation

A great AI or ML model is worthless if it can't be delivered in a scalable, cost effective and technically sustainable way. Find out how.

Data Science at Scale - 10% AI, 90% Engineering

A great AI or ML model is worthless if it can't be delivered in a scalable, cost
effective and technically sustainable way. Our data science team excels in the
design and implementation of machine and deep learning models for the analysis
of data and media at scale.

Data Science seems to have something mystical about it, to the extent that
enterprises have almost come to consider it as a magical solution to impossible
problems. The reality is that behind DS there are tons of unfashionable data
engineering and analysis tasks, before statistical models can be applied to the
problem. 

Our team of talented experts here at Data Language can leverage years' worth of
technical excellence to ensure your AI solution can actually be scaled and
delivered at the highest standards of software engineering.

Understand your data 
Unlock the full potential of your data through early discovery, analysis, and
visualisation.

Learn fast
With so many variables to tweak, rapid feedback and short iteration cycles are
imperative to an effective delivery.

Models are software
As with any piece of code, statistical models also benefit from engineering best
practices for delivering at scale, with controlled total cost of ownership.

--

Read our white paper on rethinking how you do data science in your organisation:

 
[https://datalanguage.com/static/whitepapers/rethinking-data-science-in-the-enterprise.pdf]

News, features and updates about our Data Language AI Products. Find out how our AI Products solve common specialist and scaling problems.

News, features and updates about our Data Language AI Products. Find out how our AI Products solve common digital transformation challenges.

Data Language AI - News and AI Product Updates

Data Language AI

Data Science at Scale

You are missing huge opportunities available in your "video moments", when your user is thinking "I want to buy / go / know / do / watch"! Use Data Moments.

Video Micro-Moments: Meet user needs: Buy, Do, Go, Know, Watch

If you are in the business of creating high production-value video, you spend a
lot of valuable expertise, time and resources creating the video.

With conventional video publishing, the only part of this that is accessible and
usable for your viewers is "the whole video" – you are missing countless
opportunities available in your "video moments".

How can you unleash the value that you have locked into your amazing video
moments?

Use Video Micro-Moments
Meet user needs at scale, across your video and brand portfolio, using our SaaS
product Data Moments [https://datalanguage.com/products/datamoments] to create
your Video Micro-Moments.

With Video Micro-Moments you can offer your user relevant information ("Making
thyme-flavoured oil, shown below) or the very products that are being used (the
pestle and mortar, shown below), right in the very moment when they are needed:

Use our activated Data Moments [https://datalanguage.com/products/datamoments] 
video moments to meet user needs, exactly when they are thinking "I want to do"
or "I want to buy" or "I want to know".These video moments also surface in
search engines, and can be shared on social media, fully unlocking the potential
of your video content.

Data Moments [https://datalanguage.com/products/datamoments] - Activate Your
Video
Our Video Moment product Data Moments
[https://datalanguage.com/products/datamoments] enables you to activate your
video moments to meet every user's needs when it matters most - in the moment! 

Get in touch for a demo.

Video Micro-Moments: Meet user needs, in the moment

Data Moments [https://datalanguage.com/products/datamoments] is a video product
that uses structured data to activate video moments. It makes video more
discoverable to customers, and more attractive to advertisers. Created by the
team at Data Language [https://datalanguage.com/], it is built from years of
experience in metadata and digital video publishing.

What is Data Moments?

Datagraphs Logo on Dark

Data Moments Logo on Dark

Data Language AI Logo on Dark

Data Moments is our Video Moment Product. It activates video moments and creates experiences to increase video reach, engagement, and brand activation. 

Data Moments - Activate your Video

The last decade has seen an explosion in video content creation. 

But with video now everywhere, much of the potential value of that video is
lost. 

Companies are increasingly looking for solutions to make their video content
more discoverable to their customers and more attractive to their advertisers.

Data Moments is the next evolution in video marketing
Using Data Moments, we maximise the potential of key moments in your video and
in turn creates 2 key advantages:

 1. Your video now has many completely new SEO opportunities - one for every
    moment meaning your users can find each video moment via a Google search.
 2. While conventional video advertising can be both disruptive and irrelevant,
    Data Moments allows brand activation at a logical time, creating
    opportunities for sponsors or advertisers provide    users in a video with
    what they want, when they want it.

And of course, measuring your ROI is essential. All these results can be viewed
by you when you attach Data Moments to your video content. 

The long and short of it, Data Moments can turn your passive video viewers into
valuable high-intent users.

Data Language AI Strapline

Data Language AI Logo

Data Moments Strapline

Data Moments Logo

Data Graphs Strapline

Our products work together to accelerate digital transformation, and to lower the cost of innovation: Data Graphs, Data Language AI and Data Moments.

Products by Data Language - Data-led Digital Transformation

Our products work together to accelerate digital transformation, and to lower
the cost of innovation.

Our Products

We are developing our Text AI Media Classification Products to help Cochrane automatically classify Clinical Studies onto Snomed-CT and PICO structured data

AI Classification of Clinical Studies with Text AI to fight Covid-19

We've just received the green light on this public-funded innovation project,
bringing two areas of significant Data Language expertise into play to help
combat Covid-19.

The mission combines two of our favourite things:
1. Clinical Evidence Knowledge Graphs
We've been working with Cochrane on their knowledge graph and data strategy
[https://datalanguage.com/blog/how-knowledge-graph-technology-is-helping-cochrane-respond-to-covid-19] 
since we started the project with them in 2014. As part of this, we recently
helped them launch their Covid-19 Study Register
[https://datalanguage.com/blog/covid-19-rapid-response-technical-delivery-at-cochrane]
, which summarises the current state of Covid-19 clinical evidence from around
the world that has been released into the public domain via authoritative trial
registries and journal databases.

2. Our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] for
automated text classification
Over that time, we have also cemented our position as industry leaders in
machine learning text classification and analytics, and have developed
particular expertise in high volatility domains (e.g. academic research,
breaking news, R&D) and complex ML engineering challenges. This led us to
creating our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services].
[https://datalanguage.com/tagmatic-ai-document-classification]

Mission: to ensure Covid-19 clinical decision making is informed by the latest,
most comprehensive reliable evidence possible.
With the help of the UKRI [https://www.ukri.org/], Digital Catapult's Machine
Intelligence Garage
[https://www.digicatapult.org.uk/for-startups/acceleration-programmes/machine-intelligence-garage]
, and Innovate UK [https://www.gov.uk/government/organisations/innovate-uk], we
are now bringing our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] into play
with our subject matter expert partner Cochrane to help the fight against
Covid-19.

We will be launching this new HealthTech AI beta before December. 

Get in touch if you want to know more.

Automated Classification of Healthcare Evidence

Scopa Logo

Luminery Logo

Luminery website

Datagraphs Logo

Data Graphs website

Shoppable moments are when users are given the utility they need to buy a
product that they see in the video, in the actual moment when they see it. This
can be achieved using technology that allows users to click directly to an
e-commerce product offer page from that video moment, or to "Add to cart" in
that video moment.

What are Shoppable Moments in Video?

Video moments connect the user to what they want when they actually want it. For
example, we show the user a product that is featuring in a video when they are
likely to actually want to buy it. This is in total contrast to the outdated
video Ad paradigm of randomly interrupting user experiences with unrelated
products when they do not want to buy them (and while tracking them around the
internet).

Why do Video Moments work better than Video Ads?

Video Moments can be used to meet user needs when they are at their strongest.
In the case of Products, you can provide a product moment to show the e-commerce
destination that offers a specific product at the exact moment that it is being
used or demonstrated in the video. This harnesses the strongest user intent, and
typically saves the users many clicks and search tasks.

How can Marketers use Video Moments to sell products?

Video Moment Technology enables Publishers, Brands and Product Retailers to add
new utility and commercial opportunity at a video moment level. Structured video
moment metadata is used to connect new highly contextual user experiences, brand
promotion opportunities, and to remove the reliance on cookie-based user
tracking and conventional video Ads.

What is Video Moment Technology?

of Video Micro-Moments generated by Data Moments
[https://datalanguage.com/products/datamoments] for the Rugby World Cup were
listed in the first page / top 10 of Google Search Results (SERPs). Statistic
source: Data Moments video key moments on Rugby World Cup 2019, for J SPORTS
[https://datalanguage.com/news/luminery-on-rugby-world-cup].

new interactions with Video Moments for every 100 video views on Jamie Oliver.
These are brand new interactions meeting user needs in Micro-Moments, that video
publishers did not have at their disposal previously. Statistic source: Data
Moments on Jamie Oliver videos
[https://datalanguage.com/news/luminery-video-moments-on-jamie-oliver-results].

CTR on Video Plays for Product "I want to buy" Micro-Moments on Jamie Oliver
Videos. This is 10 x the Video Pre-roll Ad standard of around 0.5% CTR.
Statistic source: Data Moments on Jamie Oliver videos
[https://datalanguage.com/news/luminery-video-moments-on-jamie-oliver-results].

5.4%

Analysis of 1 month of video stats from Jamie Oliver Christmas videos shows 10x CTR on Data Moments, and extremely high engagement rates.

Data Moments shows benchmark-beating stats on Jamie Oliver videos

Data Moments is a new type of video experience, where users can interact with
moments in video. For Jamie Oliver, this means getting more from each step in a
recipe video, and highlighting products that are used in the video so that
viewers can buy them directly.

This image shows a "Making thyme flavoured oil" video moment, that had an
interaction rate of 62%.From a data sample of 1 month of Data Moments on Jamie Oliver video
[https://datalanguage.com/news/jamie-oliver-christmas-videos-enhanced-with-luminery]
, here are some highlights:

Video Moment Engagement
 * Challenge: Video experiences haven't changed for years. Can we get a new,
   user-centred experience that dramatically improves how viewers use Jamie
   Oliver videos?
 * Solution: Identify steps in the recipe, and the techniques, products and
   ingredients in those steps. Activate the steps as structured "How To" moments
   using Luminery. Add important products so that users can find them directly.
 * Results: 92 new "moment interactions" per 100 video views. 9.3% Interaction
   Rate with HowTo steps (compared to the current ZERO).

Video Marketing Conversion Performance
 * Challenge: Jamie Oliver produces a range of products, and creates incredible
   recipe videos. How do we drive better product sales from these videos?
 * Solution: Identify products in the recipe and activate the moments to help
   users directly reach and buy the products at the right moments using Data
   Moments (saving huge conversion fall-off due to searching and uncertainty
   barriers).
 * Results: 5.4% CTR (clicks as % of video views) generated by the "product
   moments" (compared to 0.5% of standard pre-roll Ads). 9.6% conversion rate at
   the Ecommerce vendor destination for Jamie Oliver products.

What does this tell us?
This demonstrates, again, the benefit of using structured video moments to
activate new value in Video. We've demonstrated new engagement and revenue
-driving opportunities, and a fresh model for video publishing.

Data Moment video Stats from Jamie Oliver Christmas videos

Who is Cochrane?
Cochrane [https://www.cochrane.org/] is the global not-for-profit organisation
whose core mission is to put evidence at the heart of health decision-making all
over the world. Over 90% of WHO guidelines are informed by Cochrane’s systematic
reviews.

What is the Covid-19 Study Register?
The Register is a precisely scoped, authoritative source of the latest clinical
evidence from around the world concerning the Covid-19 pandemic, that is being
used to inform point-of-care clinical decision making and evolving healthcare
policy internationally.

Healthcare professionals can use it to locate all relevant, reliable clinical
evidence about specific healthcare questions from the latest Randomised
Controlled Trial (RCT), observational, modelling and other studies to support
the fight against Covid-19.

This crucial, trusted resource is essential at a time when the evidence base is
developing rapidly, as healthcare professionals require structured and reliable
up-to-date information.

Partners with Cochrane since 2014
We first worked with Cochrane in 2014 on a digital transformation project,
designing and delivering a radical new platform architecture centred around
linked-data and knowledge graph technologies. Since then we have worked to
refine, iterate and scale their platform to create a suite of applications to
publish evidence in healthcare using structured data.

Solid data architecture makes rapid innovation possible
This Covid-19 Studies Register is the latest example of how Cochrane is able to
innovate rapidly on the scalable knowledge graph platform architecture delivered
by Data Language. The structure and flexibility means that new use cases can be
delivered rapidly and efficiently.

See the Covid-19 Study Register here [https://covid-19.cochrane.org/].

Find out more
 * Cochrane's Covid-19 Resources and News
   [https://www.cochrane.org/coronavirus-covid-19-cochrane-resources-and-news] 
   (page updated regularly).
 * More about Cochrane and the rapid delivery of the Covid-19 Study Register
   project
   [https://datalanguage.com/blog/covid-19-rapid-response-technical-delivery-at-cochrane]
   .
 * Our work with Cochrane since 2014 - Information Architecture, PICO Ontology
   and more
   [https://datalanguage.com/blog/how-knowledge-graph-technology-is-helping-cochrane-respond-to-covid-19]
   .
 * More about our Knowledge Graph Engineering
   [https://datalanguage.com/knowledge-graph-engineering].

A knowledge graph is a collation of information and data typically within the domain of your business context. The information is stored in a database, often a graph database such that it can be queried, maintained, and interacted with by humans or machines. We have exceptional experience in the design, implementation and deployment of knowledge graphs. We have been working with graph databases since our inception and have delivered knowledge graphs solutions for global organisations.

We have exceptional experience in the design and implementation of knowledge graphs and have delivered knowledge graphs solutions for global organisations.

Knowledge Graphs - our Work, Features, News and Updates

Knowledge Graphs

Launching the Cochrane Covid-19 Study Register

Our pitch included using our Explainable AI Platform to provide London's analysts with explainable AI (XAI) decision support.

Explainable AI Platform at London Civic Innovation Challenge

We've just been at City Hall for London's Civic Innovation Challenge Awards
Ceremony. Sadly we didn't win on this occasion, but we were proud to be in the
finalists for the Counter Violent Extremism Social Tech Challenge.

Explainable AI Social Tech to help Londoners
Our pitch included using our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] to
provide London's analysts with explainable AI (XAI) decision support.

Explainable AI decision support - in this case for violent extremism specialists
Thanks to the GLA Team and Social Tech Trust!
The finalists with the GLA team and Social Tech Trust.

News and Product Updates about our Explainable AI Platform (XAI)

Explainable AI (XAI) means that the process, reasoning and decisions made by the AI are transparent and clear to the users and teams involved. Even before this became a trending technical jargon term, we were delivering Explainable AI products and services.

Updates and news about our Explainable AI Platform (XAI). We are specialised in moving new AI services to production rapidly, avoiding pain points in XAI

News and Product Updates about our Explainable AI Platform (XAI)

Explainable AI Platform

Proud Finalists in London's 2020 Civic Innovation Challenge

Nicola Donadoni

Simplicity as competitive advantage. Simpler is better. As simple as that.

Techniques for hypothesis validation and minimisation of negative outcomes are
utilised throughout the design and execution of the technical strategy.

Effective evolutionary technical strategies that are continuously aligned to
business propositions.

Data Language Text AI Services can be applied to almost any text classification
problem, and are ideally suited to domains such as News, Sport, and
Lifestyle/Entertainment Publishing. Importantly, our Text AI Services also work
in Law and Legal tech for classifying legal texts, contracts and clauses, and in
Healthcare and Life Sciences for classifying documents against bioinformatics
vocabularies such as SNOMED-CT, MeSH, and MedDRA (as a Computer Aided Coding
System).

What sectors do Data Language Text AI Services work for ?

Data Language Text AI Services are incredibly easy to integrate. They have
powerful APIs for training and prediction. Documents are sent to the training
endpoint for on-the-fly training, and sent to the predict endpoint for
sub-second rapid prediction. We also have a visual playground that can be used
for experimenting, and trialling the services. All the infrastructure is managed
by us, you can be up and running in just hours.

How do I integrate Data Language Text AI Services with my publishing system ?

Data Language Text AI Services are language and character set agnostic. They
work out-of-the-box on all latin character set languages, as well as Cyrillic,
greek, Arabic, and any other alphabet based language. They have not yet been
deployed on Chinese and Japanese Kanji, but if you have a project for
classification of Kanji text, we would be happy to work with you.

What languages do Data Language Text AI Services support ?

Data Language Text AI Services are commercial SaaS tools for sophisticated,
language agnostic text classification and recommendation using AI and machine
learning. They are fully managed cloud services, that use your own dictionaries,
taxonomies, vocabularies or knowledge graph entities. They are built on pure
machine-learning algorithms and thus avoids problems such as disambiguation.
They are self-optimizing, and evolve as your content evolves.

What are Data Language Text AI Services?

The outcome of domain modelling is a set of related conceptual models and a
ubiquitous language. A domain model is one of potentially many models that
describe your organisation's core business space. If a project team designs,
writes code or acts on a strategy with a shared understanding of the domain, it
reduces project risk and can improve the quality of the software being
developed.

What is the outcome of domain modelling?

Domain models are supposed to grow and change as the problem space evolves. We
often start an engagement with a big picture view of an organisation's domain.
This helps everyone understand the process and its potential value, as well as
setting more focused sessions in context. As a product moves into a discovery
phase, a key part of discovery becomes understanding the domain and developing
the ubiquitous language of the team. It is key here that we attempt to keep the
models as small and loosely coupled as possible. In DDD we will talk about
bounded context and avoiding designing all encompassing enterprise data models.
Enterprise scale data models tend to work against the goals of making the domain
easy to communicate to others and retaining model flexibility over time.

How does domain driven design fit into the product life-cycle?

For products that deal with complex domains, the team's collective ability to
learn becomes the most significant constraint. It also presents the largest risk
as ambiguity or lack of domain knowledge compound errors in the system. These
types of errors tend to be expensive to fix if caught late. By refocusing the
project on its primary domain design decisions can be made which are informed by
a shared team understanding.

Why is domain driven design important to product development?

Domain-driven design is the process of optimising a team's ability to learn about the domain it is working in. Find out more here.

How do I do Domain Driven Design? by Data Language

Domain-driven design is the process of optimising a team's ability to learn
about the domain it is working in. Documents are often places where we can hide
our ignorance about a domain and DDD discourages the over reliance on
documentation. Domain modelling sessions will most likely take place in front of
a whiteboard where the team and subject matter experts will draw back at each
other using illustrative examples from the problem space. Through this
exploration of the domain team members reach a consensus in their understanding.
This consensus (or ubiquitous language) is the foundation that development work
can then build on. In a complex domain you will need to conduct many sessions to
capture different perspectives and establish how meaning changes between
contexts and edge cases.

How do I do domain driven design?

We take you through a quick explanation of Domain Driven Design, the process of optimising your team's understanding of the domain they work in.

What is Domain Driven Design/Domain Modelling/a Domain Model?

A domain model is a conceptual model which results from the activity of
domain-driven design. The conceptual model will often be represented as an
entity relationship diagram. It is important to note that domain-driven design
puts less emphasis on the documentation but rather on the collective learning
that the team gains from the process. This helps reduce the risk of expensive
mistakes being made late-on in a project where they have become encoded in lines
of code or data models.

What is domain driven design? (domain modelling/domain model)

GraphQL is a contemporary API technology developed by Facebook. Typically it is
used for querying, manipulating and serializing JSON data structures. Until
recently (as of Jan 2020) it was not normally associated with the querying of
graph databases, but a number of graph database vendors are now providing
GraphQL API interfaces alongside the native query languages like SPARQL and
Gremlin. While it is a very high utility, and extremely developer-friendly API
technology, it is not as expressive or as fully featured as the native graph
query languages.

What is GraphQL, how does it relate to Graph Databases ?

The method of querying a knowledge graph depends on its implementation, they are
typically queried using one or more dedicated query languages. A knowledge graph
built upon a labelled-property architecture (e.g. Neo4J) is typically queried
with either Cypher or Gremlin. A RDF based graph (e.g. GraphDB or StarDog) is
queried using SPARQL. Graph database vendors are also starting to provide
GraphQL interfaces as a query mechanism, but this does not provide the
expressiveness and feature-capability of the native query languages. These query
languages are typically aimed at developers and data specialists, for business
users, the ability to navigate and ask questions of the graph is typically
abstracted into microservices, search interfaces, visual graph explorers, or
tailored user-experiences to meet specific use-cases.

How do you query a knowledge graph ?

Graph Databases come in two main archetypes: Labelled-Property Graphs (LPGs),
and Resource Description Framework (RDF) based graphs.

With a labelled-property graph, nodes and edges both can have metadata
(properties) assigned to them in the form of key-value pairs. They are tuned for
querying and analyzing Paths through the graph, and do not typically support
semantic reasoning.

RDF based graph databases are based upon the W3C RDF standard, and store data in
the form of triple-statements (subject-predicate-object). The predicates
(relationships) that join nodes together confer semantic meaning upon the data.
RDF graph databases can be reasoned upon, and can infer new assertions
(statements) from the semantic data model.

What types of graph databases are there ?

Last updated: 25th May 2018

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Privacy Policy

A graph database is a NOSQL database based on graph-theory that stores data in
indexed collections of nodes and edges, where the nodes represent domain
entities, and the edges represent the semantic relationships between the
entities. Node-Edge-Node relationships (statements) can be chained to create
navigable arbitrary-length paths through the data. Graph databases can be
queried using one of a number of query languages depending on the database
implementation type. They can typically store many billions of assertion
statements, and are often used as an implementation technology for knowledge
graphs. Graph databases typically form the foundation of a knowledge graph - but
not a necessary requirement.

What is a Graph Database ?

Knowledge graphs are becoming an important and integral part of an
organisation's data landscape. They provide a human and machine readable
database of all the things of interest to the enterprise in their domain. The
knowledge graph typically describes the domain entities and the semantic
relationships between them. It provides interfaces to query the graph as
structured data to drive products and user-experiences both internal and
external to the organisation. It is evolvable, and the knowledge stored can grow
and mutate as the business itself grows and changes. Its value lies in its
ability to allow an organisation to ask questions of the things it cares most
about.

What is a Knowledge Graph ?

We benchmarked our Tagmatic service against Hansard data: a corpus of ~200,000
parliamentary interventions for the 2005/6 period , classified with ~7200
categories, F1 scoring a whopping 0.83

0.83

Data Language have been fantastic working with us to develop a set of domain
models. Through this process we were able to design a coherent set of ontologies
to enable new innovative data driven products.

Parliament

Data Language have a very high level of knowledge in data modelling and overall
skills in technical architecture and semantic workflows.

Data Language have helped Cochrane transform from a document centric
organisation to a data centric one. Their knowledge of linked data and data
strategy is world class. They deliver.

Cochrane

The Google knowledge graph contains over 1 billion entities, and 70 billion
facts (assertions) about those entities. The majority of Graph Databases today
will comfortable scale to many billions of statements.

The Linked Open Data Cloud [https://lod-cloud.net/] contains some 1,239 datasets
such as Wikidata, DBpedia, Geonames, IMDB, BBC Music, data.gov.uk, across
domains including media, life-sciences, government, social and geography.

1,239

We helped Cochrane develop a knowledge graph for evidence-based health care with
some 350k concepts covering populations, interventions and outcomes, linking to
industry biomedical vocabularies such as MeSH and SNOMED-CT.

350k

 * Make more of your video content for use across multiple channels
 * Track the impact of your campaigns more accurately and show ROI
 * Increase web traffic and SEO
 * Allow viewers to navigate quickly to individual moments for an optimised
 * viewing experience

Marketers & Content Creators

 * Capture the video moments that best showcase your brand
 * Integrate contextual commerce product ads for instant ROI
 * Use video content across multiple channels for maximum reach

Social Media Managers

 * Integrate product and brand ads without impacting viewing experience and
   reduce risk of ad blockers
 * Control the products you advertise - integrate with many online shops
 * Achieve up to 20% conversion on Amazon

Advertisers

We have built success on strong working ethics and constant pursue of
excellence. We have a dynamic, lean, organisational structure the ideal
environment for driven talent to develop, raise and thrive.

We take our professional mission very seriously, but also believe that an easy
going, relaxed environment makes the best setting for people to reach their full
productivity potential in their own style. We foster continuous learning,
incentivise initiative and creativity, and reward out-of-the-box thinking. We
are tremendously focused, and equally affable.

Join Us

Modelling and experimentation are only part of the fun. Taking an idea to
production is a journey through a wide range of software engineering challenges.
Take your passion for AI to the next level.

ML engineer

Before making tea you think of a test for it, and make it fail first? We want to
hear from you.

Full stack developer

About gallery image 5

About gallery image 4

About gallery image 3

About gallery image 2

About gallery image 1

 * Increases consistency
 * Speeds up content classification of large archives
 * Reduces resource requirements and team workload

Archives and libraries

 * Automates document or part of document classification
 * Can classify against bespoke or open taxonomies
 * Reduces resource requirements and team workload

Regulated industries (e.g. legal & healthcare)

Data Science. Engineered
To deliver useful data platforms, you need to be great engineers as well as
brilliant data scientists.

At Data Language we combine vast experience in technical solutions engineering
with cutting edge data science. This allows us to not just do magic with data,
but build systems that are robust, scalable, and maintainable.

Whether it's big data, linked data, machine learning or AI, we design and build
practical and pragmatic technical solutions.

What we do

Data Language helped Euromoney distill a broad and complex enterprise
engineering problem into a deliverable technical and data strategy. I would be
happy to recommend them to anyone.

Euromoney

Our Tagmatic text classification AI platform scales to >100k parallel predictive
micro-models, and returns an ensemble prediction result in under 1 second.

100k

Scalable enterprise data science is 10% AI and 90% engineering.

Petar Zdravkov

Luis Amador

Neha Thaker

Steve Liles

Fabio De Nigris

Lauriane Kayungu

Adam Knight

Anthony Huges

Fabio Colasanti

Silver Oliver

Julian Everett

What is governance if not the continuous struggle against the natural tendency
of things to get messy? The second law of thermodynamics is definitive: if left
unattended, or poorly looked after, systems tend to get chaotic - and we all
have plenty of empirical evidence of this surely! The key to governance is
striking the right balance between naturally opposing forces: the complexity of
systems, and the energy required to keep said systems in the desired state.

Once expressed in these terms, governance boils down to two simple axioms: keep
things simple, and design your processes carefully. Over the years we have
refined a scalable, lean framework for change management that, coupled with the
right technical architecture, has proven to be highly successful in managing
complex systems for multi-matrixed organisations.

Establishing an effective technical governance can be a daunting exercise.
Multi-matrixed organisations, fluid start-ups, consolidated enterprises - all
have different challenges but the same risk to end up entangled in convoluted
processes that slow down efficiency and hinder commercial opportunities.
Governance is a fine balance, we can help to strike it.

Technical governance

We believe different jobs require different technologies, design patterns and
implementation techniques. There’s no such a thing as a one-size-fits-all silver
bullet, no fairy dust. That’s why we are always on top of latest trends and
technologies to offer you the best possible solutions out there.

We also believe that, in an ever-changing digital marketplace, top quality
software solutions are those that come with a high degree of evolvability and
low Total Cost of Ownership.

As a result, we go out of our way to ensure our code is fully automated, is
leveraging the latest best practices, and (most importantly) is simple. No
wonder then we consistently produce extraordinarily high quality code, is it?

Whether you have an in-house development team, or no coding capability
whatsoever, we stand by you throughout the execution of your technical strategy.
We have helped clients recruiting, training and leading software developers of
different seniority throughout the software delivery. And of course, we’ve
enjoyed building software with them.

Full-stack engineering

Information Architecture is a difficult practice to define, let alone master.
For some it is synonymous with the building of taxonomies and classification
systems; others extend its scope to UI/UX, up to search and SEO. For us at Data
Language it is all the above and much, much more. Information Architecture
permeates all we do. IA is the first step on any project as an acid test for
understanding your domain and specific business scenarios. We consider
Information Architecture a sort of art, and we have come to be considered
masters in its practical application.

If that sounds familiar, we should really talk about Linked data.

Breaking free from data silos can feel daunting. We understand that. That’s why
we don’t dive into the data head first. Our designs are driven by commercial
opportunities and tailored to your specific domain. It’s primarily about a
business vision. Yours.

Information Architecture

All too often, data lakes end up becoming dumping grounds for all sorts of data.
Messiness is only the first sign of degradation; lost in complexity, data is
soon too difficult to mine; the information flow is now just a feeble brook, and
stagnation is around the corner: you have a data swamp. We believe in data as a
continuum, powerful stream of information where Big and Fast are opportunities
rather than challenges.

By applying a thin layer of semantics on top of your big data solution, we will
enable smart data lakes which are connected, meaningful, governable. Kiss
goodbye to siloed reservoirs, and leverage the business advantage of a
distributed, dynamic, scalable source of knowledge. Let the data flow.

Too many companies out there offer Big Data solutions rooted on old paradigms.
When it comes to insights mining, governance and cross-pollination of data, we
believe a little bit of semantics goes a long way. Your Big data solution won't
look the same and big wont be big enough.

Big data

Data Science seems to have something mystical about it, to the extent that
enterprises have almost come to consider it as a magical solution to impossible
problems. The reality is that behind DS there are tons of unfashionable data
engineering and analysis tasks, before statistical models can be applied to the
problem. A great model is worthless if it can't be delivered in a scalable, cost
effective and technically sustainable way.

At Data Language we don't just excel in the delivery of Machine Learning
solutions, we can leverage years' worth of technical excellence to ensure your
AI solution can actually be delivered at the highest standards of software
engineering.

Jamie Oliver uses Data Moments

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