Common Data Standards for Uniformity and Interoperability on Digital Platforms
Vinay Lopinti
e-Governance Specialist || Expertise in G2C, G2B, G2G Solutions || Driving Digital Transformation & Data-Driven Decisions for Government Initiatives
1. Introduction
Government departments often work in isolation, which results in fragmented data systems that prevent seamless sharing and exchange of information. This siloed approach highlights the crucial need for improving data interoperability among departmental applications. To achieve this, it's essential to establish common data standards to ensure accurate interpretation and exchange of information across various systems. Data standards provide an agreed-upon set of terms and rules for defining and sharing data, promoting consistent data recording, and efficient data exchange. They also enable data to be reliably read, sorted, indexed, and communicated between different systems. Standardizing data formats is crucial for the systematic development of e-Governance applications and the optimization of government operations. Implementing common data standards brings numerous benefits, including enhanced data quality, reduced duplication of efforts, and improved decision-making processes within government agencies. Moreover, it fosters interoperability, enabling seamless data exchange among diverse applications and systems. However, alongside establishing common data standards, it's essential to prioritize data protection and privacy. Balancing data availability and usability with robust measures to safeguard data privacy and integrity is crucial to ensure compliance with relevant regulations and standards.
2. What are Data Standards?
Data standards are formal guidelines that establish a common structure, format, and definitions for data across various systems and organizations. They ensure consistency and accuracy in data, leading to improved data quality and reliability. By promoting interoperability, data standards enable different systems and applications to understand and exchange data seamlessly. These standards provide clear guidelines for data collection, minimizing errors and reducing data redundancy.
Key features include specifications for data element names, definitions, formats, and usage guidelines, often supporting electronic reporting and data transmission. Adopting data standards is essential for organizations to share accurate, complete, and consistent data, enhancing data access and making it a valuable asset for improving overall data management.
3. Objectives
The following objectives are established to investigate the significance of common data standards in promoting data uniformity and interoperability.
4.? Use cases
The development of common data standards is essential for effective data management across various government departments. Standardized formats and protocols reduce redundancy, ensure consistency, enhance reliability, and improve data protection. They also enable seamless communication and collaboration between departments, streamlining data exchange and fostering interoperability. Standardized data facilitates cross-departmental analysis and reporting, allowing agencies to derive valuable insights and make informed decisions based on comprehensive data. ?The importance of common data standards is elaborated with various use cases below.
Use case-1: Beneficiary Data Integration
For instance, beneficiary details across different departments and different service providers can cause an increased incidence of duplicate records and sub-optimal results for matching algorithms. For departments building their own systems, a standard-driven approach will prevent many potential issues in integrating data, migrating legacy systems, and redesigning existing data stores. Consistently following standards for data formats at the point of capture or data entry is crucial to preventing ambiguous beneficiary identity. For example, entering a birth date in MMDDYY format instead of MMDDYYYY format (when not taken from Aadhaar Service) can lead to potential errors.
Use case-2: Agriculture Data Management
For instance, when trying to predict the yield of a crop, we require certain parameters such as the area sown, weather data, soil properties, and groundwater level. However, the data captured by each department varies in terms of parameters, frequency, representation, access, and distribution. This lack of consistency poses a significant challenge to the efficient management and utilization of the data.
Use case-3: Masters Data Management
There appears to be a lack of consistency across departments regarding the maintenance of data, as different master codes are being utilized. This inconsistency is evident in Table-1, where varying codes are being used for the same districts among departments. This incongruity can pose challenges when attempting to analyze cross-departmental data and exchange information.
?In today's fast-paced world, there might be a case were departments to have an complex network of interdependent applications developed by multiple service providers and developers over many years who typically worked on just one or a few of these applications. Unfortunately, this can lead to fragmented systems and siloed development within the department. Over time, many of these service providers/developers move on, which leads to silo development and disparate systems within department.
Data silos are significant barriers to inter-departmental collaboration, accessibility, and efficiency, reducing productivity and negatively impacting data integrity. It is important for departments to take an active role through data governance in considering and approving data standards. If a department can successfully implement a collaborative approach among departments, it can define a systematic, governed process for developing, institutionalizing, promoting, and enforcing standards that are in aligned with departmental objectives.
The use of data standards enables reusability of data elements and their metadata that can reduce redundancy between systems, thereby improving reliability and often reducing cost. Data standards ensure consistency, and uniformity in code set use by providing for the maintenance and management of permissible code sets.
The following benefits accrue to the common set of data standards after they are created, disseminated across departments, and upheld by proactive governance:
5. Development of Data Standards
As suggested in the India Data Accessibility and Usages Policy (IDAUP, 2022), the State Data Office (SDO) is the focal point for developing, consolidating and publishing of Common Data Standards. The process involves seeking guidance, input and participation from a diverse group of stakeholders. Common Data Standards involves two main aspects - developing technical standards and communicating with stakeholders to encourage adoption of these standards.
Identification of Common Master Data Parameters (CMDP): The State Data Office ensures the interoperability of information related to beneficiaries collected by various government and non-government organizations to confirm data integrity for smooth data exchange across the departmental applications (for example refer to use case 4). The following are Common Master Data Parameters to uniquely describe characteristics of a beneficiary but not limited to:
Issuance of Common Masters and Coding Systems: The State Data Office issues Common Masters with the following coding systems but not limited to:
The State Data Office shall make available the Common Masters through API to any Stakeholders, Government Departments and other agencies.
6. Data uniformity
Data uniformity is critical when capturing data at agreed-upon intervals in order to maintain sector-specific units of scale, avoid record duplication, and avoid erroneous errors. The State Data Office ensures that the data from various departments is consistent. An indicative list for logical uniformity of data but not limited to:
7. Data interoperability
Data interoperability is the real-time exchange of data between systems that communicate directly in the same language. It protects semantic data exchange through predefined and delivered contexts, structural data exchange through models, structures, & schemes, and syntactic data exchange through common formats, encoding, decoding, and representation (for example, see use case 4). The State Data Office ensures data interoperability among departments through Application Programming Interface (API), which allows data to be automatically shared between applications and departments at the granular level. When sharing API data, departments must adhere to the following standards, which are not limited to:
a) GET type
b) POST type
Example: Use a domain name in the endpoint, like "https://example.com/data".
a) API endpoints must contain associated information.
b) Example: When sharing data for the state of Haryana, nesting could be as shown: "https://example.com/statedata/haryana".
Ports should be limited to 80 and 443.
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If any header needs to be passed with the endpoint, it must be shared.
If any parameters need to be passed with the endpoint, they must be shared.
a) If anybody needs to be passed with the endpoint, it must be shared with its type.
b) Example: "form-data", "x-www-form-urlencoded", or "raw - json", "raw - xml".
a) Details of any authentication/authorization needed to access the API must be shared.
b) Authentication mechanisms such as OAuth 2.0 or API keys should be used.
APIs should adhere to RESTful principles (Representational State Transfer).
Secure communication should be ensured through HTTPS.
API versioning should be implemented.
Documentation should follow OpenAPI (formerly Swagger) standards.
Response formats including JSON (JavaScript Object Notation) or XML (eXtensible Markup Language) should be supported.
Support for pagination and filtering parameters for large datasets should be provided.
Error handling conventions with appropriate status codes and error messages should be established.
Rate limiting mechanisms should be in place to prevent abuse or overload.
Compliance with relevant data protection regulations such as GDPR or HIPAA is necessary.
A sample response body should be shared to provide insight into the data being shared.
Frequency (daily, weekly, monthly, or yearly) of data requests must be shared.
The State Data Office sets data sharing standards. An indicative list of acceptable formats but not limited to:
By implementing the above common data standards with the assistance of the State Data Office, departments can benefit from streamlined processes, reduced administrative burdens, and enhanced data accuracy. The State Data Office serves as the central hub for developing, consolidating, and disseminating these standards, ensuring consistency and interoperability across departments. Adopting these standards allows departments to enhance data management practices, facilitate seamless data exchange, and empower informed decision-making. Furthermore, common data standards facilitate efficient resource allocation, foster innovation in service delivery, and improve transparency and accountability in government operations.
?8. Use case-4: Education Platform - Student Data Integration across departments
The use case-4 shows how Student-A, a high school student, navigates through different academic phases while benefiting from data interoperability enabled by common data standards across various educational applications and departments.
Student-A enrolls in a new school and provides their Aadhaar number during the admission process. The school's enrollment application integrates with the Aadhaar Services API to validate the Aadhaar number and retrieve important student information, such as name, date of birth, father's name, address, gender, and photo, resulting in a Child Information ID for unique identification.
For board exams, the same Student-A information is obtained from the school's database using the Child Information ID. The 10th board exams application obtains student information such as name, date of birth, gender, religion, and medium through API integration with the school's database. Similarly, for 12th board exams, additional information such as school name, marks, division, result, stream, and year of passing is retrieved from the 10th board exams database.
During common entrance exams, the application integrates with both the school's and board's databases to access comprehensive student information, including exam details. Integration with other APIs validates additional details such as income, caste, and residence, ensuring data accuracy and authentication without requiring Student-A to enter redundant information.
The use of common data standards benefits both students and educational departments in administration. These standards simplify processes for students like Student-A by reducing and eliminating redundant data entry tasks across academic phases. This integration ensures that students have consistent access to accurate information. In addition, common data standards improve data accuracy and consistency, reducing errors and discrepancies in student records. This improvement in data quality facilitates better decision-making processes for departments, promoting transparency, efficiency, and accessibility in educational operations. Finally, common data standards help to improve administrative workflows and effectiveness, allowing for better resource allocation and operational management across departments.
9. Conclusions
The current lack of alignment of standards for key data elements hampers our efforts to share information quickly and consistently. The uniform adoption of common data standards provides several significant benefits. It will:
10. References