Registration data is required in order to design, plan and deliver suitable programmes for the population of concern. Registration data analysis strengthens the overall operational intelligence for protection and solutions in an operation, helping to facilitate early identification of protection risks and highlights protection gaps as well as target resources for the greatest protection impact. See UNHCR’s Programme Handbook (UNHCR-internal use only) for more about the ways in which registration data inform and facilitate programming and planning activities and processes.
The below examples demonstrate how registration data, together with other data stored in PRIMES, can meaningfully inform programming.
Example: Upon registering a new population of concern, registration data shows that 15% of children are recorded as being unaccompanied or separated. This data should inform the Office about certain actions that should be taken to respond to the particular protection needs of this sub-group identified within the population. Actions may include some or all of the following:
Conversely, delayed or insufficient attention and analysis of registration data can lead to critical protection gaps on the ground, seriously impacting UNHCR’s preparedness, negotiating position with the host government as well as resource capacity to respond to urgent protection needs.
Example: Consider an emergency context, with new arrivals crossing the border and needing emergency shelter and assistance. If the rate of arrivals is not correctly identified through available information including registration data, a host of negative consequences for persons of concern may follow, including, for example:
Even in stable operational contexts, where the general profile of the population of concern is known and available services are well-established, registration data should be analysed for ongoing programme strengthening and planning. Consider the following examples of some of the ways in which registration data can be leveraged for effective protection programming and the pursuit of innovative solutions for refugees and others of concern:
| Focus of registration data analysis | Possible programme result |
|---|
| Skills and occupational profiles |
| Pursuit of training programmes and livelihood opportunities based on skills and occupational profiles to encourage and promote socio-economic empowerment. |
| School drop-out rate |
| Granular age disaggregation (e.g. 10-11, 12-13, 14-15, 15-16, etc.) identifying the critical ages for school drop-out informs FGD and targeted surveys to understand risks and causes and establish programmes to address them. |
| Mapping of addresses combined with mapping of services available in geographical locations |
| Identification of gaps in essential services for refugees in the location where they live and advocate for appropriate interventions. |
| Number of persons with disabilities and disability types |
| Based on number and type of disabilities recorded, engage new partners, implement targeted assistance and strengthen access to livelihood activities. |
| Rates of arrest and detention of refugees in a city or in a certain part of a city |
| If arrests are found to be more common in a certain geographical area, advocacy and engagement efforts with law enforcement personnel may be targeted to promote recognition of and respect for refugee documentation and refugee rights |
Registration data can only be usefully analysed if the data collected at registration is representative, of a good quality and regularly updated. Relying on registration data of a camp population from five years ago will likely not provide an accurate picture of the needs and circumstances of the population today, including in terms of new births, deaths and arrivals, updated locations, new protection and other needs, as well as changes in access to education, training and work. As such, a good registration system also includes mechanisms to manage its data, making it reliable and effective for planning and programming.
In order to leverage data for operational planning and programming, it is important that the right types of data are collected at the point of registration. It is neither reasonable nor effective to collect all possible data at the point of registration, however, it is possible to define key data sets and potential proxy data fields that will reliably inform specific programmes.
The quantity of data collected during registration will not be useful for planning and programming if the quality of the data is poor. There are many reasons why registration data may be of poor quality including data entry error (e.g. sex is male with relationship to focal point as sister), inadequate training (e.g. interviewers unaware when and how to update a specific need), ill-designed processes and insufficient oversight (e.g. data entry errors are not identified), cultural misunderstanding or weak standard operating procedures (e.g. cultural understanding of “uncle” is different to SOP definition and therefore applied inconsistently by interviewing staff).
In order to prevent and manage issues of data quality, several steps and processes can be taken. From a procedural perspective, standard operating procedures, training and regular monitoring and oversight help ensure that data collection is conducted in a consistent and harmonized manner. From a technical perspective, operations data managers should also conduct regular checks against the registration data. Several built-in validation rules are developed within proGres in order to identify and correct data quality problems. For example, business validation rules that define specific inconsistencies (e.g. sex male cannot be relationship to focal point sister), prompt registration users to a data quality error. In some operational contexts, data quality tools have been developed during large-scale registration activities to highlight missing fields or inaccuracies, particularly those data fields relevant to documentation. In addition to developing system checks, operations data managers can also run regular data quality scripts against registration data to identify common mistakes and errors. In some cases, it is also possible to apply batch correction against the database, while in other cases data needs to be corrected manually as it differs from record to record.
Sound registration systems and processes require built-in mechanisms to review and update registration data and other information over time. Module 8 provides detailed guidance on the need to establish continuous registration processes in order to maintain accurate and representative data.
The personal data of asylum seekers and refugees must be managed in a way that protects confidentiality and is consistent with privacy and data protection principles set out in Part 2 of UNHCR’s Data Protection policy. To this end, proGres v4 is designed so that access rights for each module are determined individually per user, based on a “need-to-know” and “need-to-use” basis. As such, proGres users can only view, enter or modify data in so far as it is necessary for them to carry out their functions.
In every UNHCR country operation, a requesting and an approving officer are tasked with assigning individualized access rights to staff members based on their functions. A framework on the segregation of duties aims to clearly define and grant the level of access that corresponds with the user’s specific role and responsibilities, in line with the Data Protection policy (para. 4.2) and related Guidance (para. 6.3.8).
Needs assessments2 involve systematically gathering and analysing information relating to the needs, conditions, and capacities of persons of concern – diverse women, men, girls, and boys of all ages, including those with specific needs – in order to determine gaps between a current situation and agreed standards. Needs assessments help understand the conditions faced by populations of concern. Registration data in proGres can support needs assessments in multiple ways:
2 For more on registration data in needs assessments, see UNHCR’s Needs Assessment Handbook
UNHCR’s Dataport is a ‘smart’ inventory of UNHCR’s current population information with real-time connectivity to proGres v4. The Dataport draws from proGres v4 to organize data according to operational needs, for example, generating real-time statistics, reports, dashboards and trends analysis with the help of indicators and attributes that cover all thematic, sectoral and case management areas. The Dataport was developed to maximize the potential of the data collected and contribute to global data analysis on displacement. It can be used by UNHCR and Partner Users of PRIMES tools, and will eventually be accessible to persons of concern as well as others looking for statistics on forced displacement.
Dataport tools include:
1. Interactive Statistical Reports
Statistical Overview, Annual Statistical Report and Resettlement Statistical Report.
2. Self-service Platform: Dataport Cubes
Dataport Cubes are a powerful tool to calculate, summarize and analyse data, to help identify correlations and causal relationships, measure changes and observe patterns and trends.
3. Self-service Platform: Power BI Reports
All UNHCR staff can view reports in the Dataport Power BI Workspace. The application can be used to connect to multiple data sources and provide visibility to users by presenting the information in a format that is timely, meaningful and actionable. You can look at current trends and standards depicted on the Power BI dashboards against goals or historical averages and develop customized pivot tables to monitor reliability of the data/trends.
Below is an example of a country operation dashboard. For more details on how to connect to the Dataport, see the User Guide (PRIMES users only).
