Data has the power to disrupt and revolutionize the way societies are governed. This data is open, non-personal, free-to-use and may be shared by anyone. Take for example city of Louisville, Kentucky in US. The city had one of the highest numbers of asthma cases in US. The AIR Louisville project is trying to change that by bringing together organizations and experts from varied field, and has developed a smart inhaler that tracks when, how often and where people face asthma symptoms. Combined with other information such as weather data, real time traffic, the city may take steps to improve air quality in identified areas.
For governments hoping to adopt open data in policy and in practice, simply making data available to the public isn’t enough to make that data useful. Open data, though straightforward in principle, requires a specific approach based on the agency or organization releasing it, the kind of data being released and, perhaps most importantly, its targeted audience
Open Data Policy
Having an open data policy enables department to institutionalize and operationalize information as an asset. Enterprise wide operationalization of managing information as an asset happens by providing consistent, interoperable, open, secure and high-quality information within data architecture and life cycle.
“Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.”
Data Inventory Schedule
The department to come up with department wide guidelines to review datasets on whether the data should be released to public or not, and what transformation need to be done to data before it is released to public. Each of the department’s component offices shall then review and classify data asset as “public”, “restricted” or “non-public” as under, and follow the process for releasing it.
Data Standardization and Methodologies
The standardization can be aided by implementing a collaboration tool across enterprise. Templates may be built to capture new data sets to receive update till further integration into other processes. The updates shall trigger a review process for further consideration. The review process must ensure Personally Identifiable Information (PII) is not risked to exposure either through single or combination of data sets.
Identify the checkpoints to capture data and create metadata necessary to support open data. The checkpoint shall align with the lifecycle of information asset. The combination helps to identify new data set in an automated process. To build enterprise data inventory, components of department need to work to gather description, keywords and other metadata necessary to assist department in identification and classification of asset.
The kind of data for publication to enterprise data inventory may range from measures for internal efficiency to external delivery of services indicated as under:
– Finance, Quality, Management Data assessment
– Communication data assessment – grievance, website stats and usages, public inquiries.
– Operations data assessment
– Systems data assessment
– Strategic data assessment
– Inspection data assessment
Department’s process to engage with customers
It is important to solicit feedback and ideas from customers. To that end, conference calls and in person engagement are may be arranged on periodic basis. Assistance may be taken from an ideation platform that shall have features to select the right ideas thereby helping organization to share & collaborate, evaluate and prioritize, develop and deliver ideas gathered from varying sources.
Prioritization of datasets
Department may prioritize the list of datasets which are key KPIs for it. Some of the KPIs may be –
· Average beneficiaries by state
· Average beneficiaries by total population
· Average work load in offices
· Average wait time for beneficiaries/ address grievances
A customer satisfaction index may be worked out and benchmarked with department and key stakeholders. The index may help organization to gauge its performance.