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Collaborate with us
You've decided to collaborate with the Integrated Data Service Dissemination (IDSD) project. Great! We're excited to have you on board. The way to start out is to prepare a CSV-W and publishing it online. There are to ways of doing this, can use csvcubed to generate CSV-W, or write your own CSV-W which conforms to our application-profile. We are targetting UK Government departments, offices, and agencies, but if there is a compelling case you can still ask to contribute to our Linked Data Store, Integrated Data Service Data Explorer.
The IDS Dissemination Service has a number of offering surrounding the disseminiation of linked data. There are no one size fits all solutions, so we will work with you to find the best solution for your data. We can:
- Review your data and advise how to get it in the best shape for publication
- Consult on your metadata, taxinomies, and code lists to align with best practise and standard vocabularies
- Host your data in our Linked Data Store from CSV-W
- Provide reviews of first publications to ensure that your team is best placed to embrace linked data
We can provide advice on how to get your data in the best shape for publication. At a minimum we start by getting the data into a tidy, observational shape cherished by analysts everywhere. From this point you'll leave the world of spreadsheets behind.
Linked data is all about the relationships between things. We can help you to align your metadata, taxonomies, and code lists with standard vocabularies and best practise. This will ensure that your data is Findable, Accessible, Interoperable, and Reusable. We can also help you to align your data with the Central Digital & Data Office (CDDO) standards for describing CSVs with Metadata.
The highest benefit of adopting linked data comes from reusing existing taxonomies. We can help you to find existing taxonomies and vocabularies that you can use to describe your data. The two main taxonomies which provide the most benefit are the ONS Statistical Geographies, and observational Time Period Notation.
Adopting ONS Statistical Geographies brings statistical discoverability to the public's desire to learn about their local area. It also brings the benefit of being able to compare data across different geographies. Using our tooling, namely csvcubed.
You can easily adopt the ONS Statistical Geographies by using a template in your metadata markup file referencing a column in your CSV using the codes you might already be familiar with (e.g. N09000010 representing the Northern Ireland county of Newry, Mourne and Down).
STATISTIC CODE,Statistic,TLIST(A1),Year,LGD2014,Local Government District,VALUE
ART,"Ambulance response time, median",2010,2010,N09000001,Antrim and Newtownabbey,442
ART,"Ambulance response time, median",2010,2010,N09000002,"Armagh City, Banbridge and Craigavon",429
...
ART,"Ambulance response time, median",2010,2010,N09000010,"Newry, Mourne and Down",431...
"LGD2014": {
"from_template": "statistical-geography"
},
...Adopting Time Period Notation brings the benefit of being able to ensure you are comparing observations from the same time periods. Using our tooling, namely csvcubed, you can easily adopt Time Period Notation by using a template in your metadata markup file referencing a column in your CSV using the codes you might already be familiar with (e.g. 2010-Q1 representing the first quarter of 2010).
STATISTIC CODE,Statistic,TLIST(A1),Year,LGD2014,Local Government District,VALUE
ART,"Ambulance response time, median",2010,2010,N09000001,Antrim and Newtownabbey,442
ART,"Ambulance response time, median",2010,2010,N09000002,"Armagh City, Banbridge and Craigavon",429
...
ART,"Ambulance response time, median",2010,2010,N09000010,"Newry, Mourne and Down",431...
"Year": {
"from_template": "year"
},
...We can also help you align your data to standardised measures and units. It's important that measures are well defined without units included in the name, that indecies are correctly expressed, and that related measures can be found quickly in a network of related measures. Expressing measures correctly requires practise, and we can continue to help you adopt the best practise as you publish your statistics.
Units are a bit easier. Most official, national, and experimental statistics use common units like numbers, percentages, currencies, times, and distances. Reusing existing units from the QUDT Unit Vocabulary and extending them as scaled units is easier when addressing them separately from their associated measure.
e.g. Pounds Sterling and Millions of Pounds Sterling are related and convertable between the two.
Expressing indices in time series requires the inclusion of a base year, but we can help with that too.
Many data publications across government include confidence and credible intervals, non-seasonal and seasonally adjusted data, and supression of observations to prevent disclosure of confidential data. Our tooling can help you to express these aspects of your data and metadata, and we can consult on how best to express your data faithfully that is both machine and human readable.
We can ingest your data into IDS Data Explorer from CSV-W files stored anywhere on the internet. We can also assist in publishing your CSV-Ws in an accessible location for us to access and to upload to our service.
In the future we will support users annoucing the publication of their data via an API so that the ingestion becomes a fully automated process.
We can review your first publication to ensure that your team has adopted the minimum standards of FAIR data. We can also provide advice on next steps, or continue to collaborate with you so that you can continue to improve your data on your own.
To find out more about how we review data, please see our review process. It is applicable to all data published on the IDS Data Explorer, regardless of source.
If you're interested in any of the services we offer, please get in touch with us at idps.dissemination@ons.gov.uk.