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Open Data Services Co-operative was established in 2015 to support organisations to publish and use open data. We have a particular focus on incubating early stage open data standards, and supporting the development of effective transparency and collaboration initiatives using well-maintained open data standards.
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Open Data Services Co-operative was established in 2015 to support organisations to publish and use open data. We have a particular focus on incubating early stage open data standards, and supporting the development of effective transparency and collaboration initiatives using well-maintained open data standards.
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We often act as the technical partner to policy-focussed initiatives, working under contract to develop and maintain open data standards, and to support standard implementation.
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Our team of employees and members work across a range of tasks:
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***Software development** - creating re-usable open source code that helps us to do our work, and that supports the documentation, implementation and demonstration of open data standards;
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***Analysis and implementation support** - working with policy initiatives, governments, non-profits and companies to equip them to publish and use open data with one of the standards we support;
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***Research and development** - supporting the development of new open data standards;
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***Training and consultancy** - addressing issues of policy and organisational change.
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-**Software development** - creating re-usable open source code that helps us to do our work, and that supports the documentation, implementation and demonstration of open data standards;
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-**Analysis and implementation support** - working with policy initiatives, governments, non-profits and companies to equip them to publish and use open data with one of the standards we support;
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-**Research and development** - supporting the development of new open data standards;
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-**Training and consultancy** - addressing issues of policy and organisational change.
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We operate as a non-hierarchical worker-owned business, committed to [co-operative principles and values](https://ica.coop/en/whats-co-op/co-operative-identity-values-principles), and to using our resources in order to provide a good place to work, to develop our staff, and to contribute to the wider community.
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We operate as a non-hierarchical worker-owned business, committed to [co-operative principles and values](https://ica.coop/en/whats-co-op/co-operative-identity-values-principles), and to using our resources in order to provide a good place to work, to develop our staff, and to contribute to the wider community.
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We are primarily funded through short and long-term contracts to research, develop and support implementation of open data standards.
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We are primarily funded through short and long-term contracts to research, develop and support implementation of open data standards.
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To find out more about working with us on an open data standards project, get in touch with [[email protected]](mailto:[email protected])
Copy file name to clipboardExpand all lines: docs/adoption/helpdesk.md
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Often the questions asked in private would make for good public discussions. A helpdesk team can translate individual implementation issues into wider forum or issue-tracker posts, and can bring together the different stakeholders who may have views on those issues. Making connections between implementers, and working to align data publishers and users, can make a difference to the success of implementations.
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Policy actors seek compliance with a standard. Users seek data usability.
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Policy actors seek compliance with a standard. Users seek data usability.
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This is a tension to manage. A helpdesk should keep in mind the overall policy goals of a standard, whilst also ensuring the technical correctness of implementations.
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**Standards are always developing**
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The documentation will have gaps. A standard will not cater for all use cases. The helpdesk are able to identify gaps, and identify ways to address them through improved resources, or by feeding into the development of schemes and related tools.
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The documentation will have gaps. A standard will not cater for all use cases. The helpdesk is able to identify gaps, and identify ways to address them through improved resources, or by feeding into the development of schemes and related tools.
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A lot of the engagements a helpdesk has can be light-touch: aiming to provide quick replies to simple questions, to help keep implementations moving. In some cases, helpdesk engagements may be more in-depth, involving multiple days of work to support an implementer in planning, executing or evaluating their data publication.
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## What?
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A helpdesk might have the following modalities of work:
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***Fielding direct enquiries** - with an e-mail address, twitter handle and instant messages going into a ticketing system, from which written replies can be sent, and through which management information on the types of enquiries and enquirers getting in touch can be logged. Enquiries may come direct from implementers, or may come from the advocacy partners seeking to promote adoption of the standard.
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***Scoping notes** - working with prospective implementers to develop a shared understand of where the standard could help, and to identify options and steps for adoption;
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***Mapping reviews** - providing templates to map existing systems to the standard, and reviewing implementer produced mappings.
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***Implementation guidance** - sharing suggestions, resources and examples to highlight relevant technical and policy approaches to implementation.
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***Data review and quality assurance** - performing automated and manual checks on data quality.
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***Training** - delivering online and face-to-face training to implementers, and to other support providers, as part of capacity and field building.
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***Tool assessment** - reviewing open source tools developed to work with the standard and providing assessments of their re-usability.
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***Technical analysis for policy advocates** - acting as a sounding board for policy and advocacy teams, to help assess the extent to which a technical implementation will meet policy goals.
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***Knowledge management** - keeping track of prospective and actual implementations, and supporting reporting about levels of engagement with the standard.
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-**Fielding direct enquiries** - with an e-mail address, twitter handle and instant messages going into a ticketing system, from which written replies can be sent, and through which management information on the types of enquiries and enquirers getting in touch can be logged. Enquiries may come direct from implementers, or may come from the advocacy partners seeking to promote adoption of the standard.
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-**Scoping notes** - working with prospective implementers to develop a shared understanding of where the standard could help, and to identify options and steps for adoption;
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-**Mapping reviews** - providing templates to map existing systems to the standard, and reviewing implementer produced mappings.
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-**Implementation guidance** - sharing suggestions, resources and examples to highlight relevant technical and policy approaches to implementation.
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-**Data review and quality assurance** - performing automated and manual checks on data quality.
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-**Training** - delivering online and face-to-face training to implementers, and to other support providers, as part of capacity and field building.
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-**Tool assessment** - reviewing open source tools developed to work with the standard and providing assessments of their re-usability.
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-**Technical analysis for policy advocates** - acting as a sounding board for policy and advocacy teams, to help assess the extent to which a technical implementation will meet policy goals.
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-**Knowledge management** - keeping track of prospective and actual implementations, and supporting reporting about levels of engagement with the standard.
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## Examples
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* The International Aid Transparency Initiative provides a helpdesk service that receives around 110 monthly support requests, as of November 2017). A number of other providers also offer support to particular segments of the implementing community (e.g UK NGOs)
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* The [Open Contracting Data Standard helpdesk](http://standard.open-contracting.org/latest/en/support/) provides e-mail support, as well as working closely with the Open Contracting Partnership to identify adopters for priority support and outreach. The OCDS helpdesk is run by two partner organisations: Open Data Services Co-operative, and ILDA, who cover support for Latin America.
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- The International Aid Transparency Initiative provides a helpdesk service that receives around 110 monthly support requests, as of November 2017). A number of other providers also offer support to particular segments of the implementing community (e.g. UK NGOs)
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```eval_rst
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.. todo::
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.. markdown::
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- The [Open Contracting Data Standard helpdesk](http://standard.open-contracting.org/latest/en/support/) provides e-mail support, as well as working closely with the Open Contracting Partnership to identify adopters for priority support and outreach. The OCDS helpdesk is run by two partner organisations: Open Data Services Co-operative, and ILDA, who cover support for Latin America.
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## Components
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A helpdesk makes use of some of the following components:
The success of an open data standard rests on its adoption. A standard with no users is hardly a standard at all. However, depending on the nature of a standard, there may be different approaches to successful adoption.
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The success of an open data standard rests on its adoption. A standard with no users is hardly a standard at all. However, depending on the nature of a standard, there may be different approaches to successful adoption.
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This section considers **the adoption curve**, different **kinds of adopters**, and different strategies to support adoption.
Adopting a policy related open data standard is generally a multistage process.
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Adopting a policy related open data standard is generally a multi-stage process.
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The Open Contracting Data Standard uses the [7-step model below to describe the process of data standard implementation](https://www.open-contracting.org/implement/#/) within the context of wider adoption of open contracting principles and practices.
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360Giving [describe a five-step data publication process](http://www.threesixtygiving.org/support/publish-data/).
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```eval_rst
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.. admonition:: For example
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:class: note
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.. markdown::
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The five steps for 360Giving data publication are:
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1. Discuss and plan
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1. Select your publishing template
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1. Prepare your data
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1. Publish on your website
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1. Register with 360Giving
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```{admonition} Example
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---
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class: note
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---
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The five steps for 360Giving data publication are:
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1. Discuss and plan
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1. Select your publishing template
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1. Prepare your data
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1. Publish on your website
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1. Register with 360Giving
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```
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At a more general level, we think about four stages of adoption, arranged as part of an ongoing cycle:
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###Commit
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## Commit
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For policy related open data standards there will often be a process for securing commitments to adopt. This might come through resolutions or motions, through public announcements, or through getting organisations to sign up to a pledge of some form. Commitments are vital to (a) understand the goals of the implementer, and align implementation with those goals; (b) help overcome technical or bureaucratic barriers that might get in the way of adoption.
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For policy related open data standards there will often be a process for securing commitments to adopt. This might come through resolutions or motions, through public announcements, or through getting organisations to sign up to a pledge of some form. Commitments are vital to (a) understand the goals of the implementer, and align implementation with those goals; (b) help overcome technical or bureaucratic barriers that might get in the way of adoption.
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###Map
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## Map
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In general, the data to be represented through a standard already exists in some system, or systems that *could* collect it exist. The mapping stage addresses the systems and business processes that will need to change to produce or consume standardised data, as well as look at the level of individual data elements to agree how data will be represented or consumed.
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In general, the data to be represented through a standard already exists in some system, or systems that *could* collect it exist. The mapping stage addresses the systems and business processes that will need to change to produce or consume standardised data, as well as look at the level of individual data elements to agree how data will be represented or consumed.
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###Build
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## Build
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At this stage the process and systems to create or consume standardised data are created. There may need to be a few iterations here to get something that produces data of adequate quality.
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###Evaluate
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## Evaluate
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One of the structural features of **open** data, is that it is often shared *before* it is used. This can mean that problems with the data are not picked up straight away, but instead are identified when someone first comes to analyse it, maybe weeks or months after the 'build' stage is complete. This is why early **review** or **evaluation** of data and data quality is vital to building a sustainable open data ecosystem. This might be manual review of data, or might come through the availability of tools that can be used to review the data resulting from the build stage (e.g. [Online Validator](component-online-validator) or [Quality Tool](component-quality-tool)).
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One of the structural features of **open** data, is that it is often shared *before* it is used. This can mean that problems with the data are not picked up straight away, but instead are identified when someone first comes to analyse it, maybe weeks or months after the 'build' stage is complete. This is why early **review** or **evaluation** of data and data quality is vital to building a sustainable open data ecosystem. This might be manual review of data, or might come through the availability of tools that can be used to review the data resulting from the build stage (e.g. [Online Validator](../components/index.md#online-validator) or [Quality Tool](../components/index.md#quality-tool)).
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