In assessing data analytics capabilities, as mentioned above, SAIC found a few instances of systems dedicated to making critical data available for analysis and decision making; however, overall, SAIC found data information assets statewide lacking. In general, however, specific systems, resources, or
BEST PRACTICE
NIEM is a key development in data architecture, modeling, and standardization. NASCIO published a recent position paper (April 2011): “NASCIO Recommends State Government Adopt the National Information Exchange Model (NIEM) to Enable Government Information Sharing.” Excerpts from the publication are provided below and many relate to both NIEM advancement as well as data management in general:
NIEM provides a broad range of products and capabilities for planning and implementing enterprise-wide information exchanges. Government effectiveness and citizen-centric government services require effective cross line of business collaboration and communication. Use of national standards will avoid redundant investment and unnecessary variation. What is needed is a common discipline for information sharing that is employed by all government lines of business. The National
Information Exchange Model (NIEM) exists as that discipline for Federal, state and local
government. NASCIO recommends that state government adopt NIEM capabilities as a component of state government enterprise architecture and data management strategy.
In general, NASCIO recommends that state governments:
• Learn how to plan an information exchange and how to employ NIEM.
• Gain support through executive and technical staff briefings.
• Train - take advantage of NIEM training – online and on-site.
• Begin to use NIEM – leverage NIEM technical support.
• Grow staff knowledge, experience, and skills through ongoing training and NIEM National Events.
• Stay connected to the NIEM site for new developments, additional domains, and continued adoption across government.
• Promote NIEM for government interoperability by adopting NIEM as part of State Government Enterprise Architecture, Data Management Strategy and Standards.
• Incorporate NIEM into Project Management and Procurement Requirements.
• Explore and evaluate inter-line of business relationships that can enhance or transform agency service delivery.
HAWAI΄IBEST PRACTICE
It was noted by more than one IT leader within the Departments that pilots that involved information sharing demonstrated the power of the data, once shared, and encouraged the organizational elements to begin sharing even more.
capabilities with the intent of supporting data analytics within the State are minimal. We found that across the enterprise, key user communities did not have
needed information available to them. Some relevant examples include:
• Department executives largely did not have quality project or operations performance data available to them at a dashboard level to effectively oversee their organizations, programs, and projects. As discussed above, the existing performance management systems were antiquated and irrelevant. DOT is an example of a
Department that expressed a specific desire to improve their ability to roll-up project information to the Department level across their major Highways, Harbors, and Airports Divisions.
• Workgroups or project teams for the most part did not have collaboration tools to more
effectively collaborate on and manage project deliverables. There are a few exceptions of efforts to implement Microsoft SharePoint as a collaboration tool in Departments (i.e., DOE, DOH, DOT, and B&F)
• Shared data at the State- or Department-wide levels was not typically organized for end-user access and reporting with the exception of some key model areas such as DOH’s data warehouse initiative.
• A strong emphasis on making information and tools available to the public (e.g., HIC, DHHL, DCCA, Lt. Governor).
Specific emphasis, resources, and investments must be managed to establish enterprise approaches to facilitate data access, collaboration, and analytics. An approach of note, worked by the State of Hawai`i’s new CIO while in the Federal government, is making available XML-based datasets for reuse and mash-ups for both internal State use as well as an “open government” initiative for citizens’ use.
The platform (or repository) for supporting this Open Government initiative in the Federal government is Data.gov. The Data.gov web site states “An underlying goal of the Open Government Initiative is to change the culture of information dissemination, institutionalizing a preference for making Federal data more widely available in more accessible formats.” As one of the flagships of the Open Government Initiative, Data.gov is designed to
facilitate access to Federal datasets that increase public understanding of Federal agencies and their operations, advance the missions of Federal agencies, create economic opportunity, and increase transparency, accountability, and responsiveness across the Federal Government – i.e., "high value"
datasets. The intention and approach for the Federal Open Government Initiative provide a model for the State of Hawai΄i to consider in adoption of data-sharing capabilities.
To Be Recommendation 15: Define Standard Enterprise Solutions for Data Sharing and Collaboration
• Establish standard enterprise solutions to implement data sharing, analytics, and collaboration. Also:
- Establish standard data sharing and analytics capabilities across
the State such as a data mart/warehouse approach to facilitate user data access, querying, and reporting.
- Establish standard collaboration solutions across the State with technical underpinnings for cross-departmental workgroup and project collaboration.
- Establish a standard management-level dashboard reporting solution with supporting data aggregation and summarization.
- Develop policies for use of emerging social media technologies and establish standard enterprise public-facing social media solutions.
Below are specific actions relative to establishing data sharing and analytics capabilities:
Recommendations Key Actions
Enterprise Data Analytics Solutions
• Establish a standard data analytics solution and approach with standard methods, skilled resources, and tools. Include approaches for user access to data such as data warehouses, marts, or portals. Include standard data replication, and extraction,
transformation, and loading (ETL) approaches,
methods, and supporting tools. Include standard enterprise ad-hoc query, reporting, and analysis tools.
• Direct the design and implementation of shared data sources for user data sharing and analytics through the use of enterprise flagship projects for implementation. Establish a State of Hawai΄i data.gov internal and public-facing web site to facilitate the sharing of
“master data sets” as defined above.
• Support internally-facing (for State use as well as application integration through web services layered on top of XML data sets) and external, public-facing (for publishing public-domain master data sets).
Enterprise Collaboration Solution
• Establish standard collaboration solutions across the State adopting technology platforms such as Microsoft SharePoint or Lotus Domino Quickr. Implement necessary technical
underpinnings and connectivity for cross-departmental workgroup and project collaboration.
Enterprise Dashboard Solution
• In conjunction with the Enterprise Data Analytics Solutions above, establish a standard management-level dashboard reporting solution with supporting data aggregation and summarization capabilities.
Enterprise Social Media Solutions
• Develop policies for use of emerging social media technologies.
(Immediate)
• Establish standard, enterprise, public-facing social media solutions, methods, expertise/skilled resources, and tools.
To Be Recommendation 15: Define Standard Enterprise Solutions for Data Sharing and Collaboration (continued)
• Evaluate and leverage, as appropriate, notable implementations of end-user data access systems to make critical data available for analysis and decision making. Specifically:
- FAMIS Data Mart – developed as a solution for end-user access to financial data from the need to mitigate constraints of the mainframe master file. The solution has served the organizations well, and should continue to be invested in and improved.
- DOH Data Warehouse – working towards integration of health-related data sets from various source organizations from disjointed, dissimilar data
structures/formats within multiple databases. The Health Information Systems Office (HISO) within DOH attests to the synergy within the user community that continues to grow as more data is integrated into the data warehouse. DOH as a whole is maturing in data standardization processes and best practices and is a model to leverage statewide.
- Juvenile Justice Information System (JJIS) – provides a single comprehensive source of information about juveniles across State and County agencies.