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Home Center for Government Interoperability Opportunities Checklist for
New Software Projects
Data Table Managment
Enterprise Focused Development

IT Blueprint For Government
by Alex Glaros
http://gov-ideas.com/


Ideas for the Future


Gov Ideas

Center for Government Interoperability

Documentation and Comments on Opportunities Checklist for New Software Projects

This page contains detailed documentation and comments regarding the checklist for opportunities when new tables or fields are designed into a business system. http://gov-ideas.com/opportunities-checklist-for-new-software-projects.htm

Correct data modeling (3rd normal form), correct keys (Data Architect, IT)

Normalizing data creates the most productive possible solutions by unlocking process oriented systems so that organizations can connect data across government to improve business processes.

Normalizing data will always produce optimal results without errors or exceptions. Less programming, faster project completion, less maintenance, fewer mistakes, more flexibility for the organization, more opportunities.

Simply bringing organizational data into third normal form resolves business problems throughout the organization and improves IT alignment to the organization's mission in the most powerful and cost effective way.

Benefits of normalization:

  • Ensures that customer requirements are properly satisfied and that new requirements are easier to accommodate
  • Makes the database easier to maintain
  • Ensures structural stability of data
  • Prevents various updating anomalies which can occur in non-normalized record structures
  • Enables record processing by a set of simple operators.
  • Elimination of redundant data storage.
  • Close modeling of real world entities, processes, and their relationships.
  • Structuring of data so that the model is flexible to give the business side agility.

Business rules should be taken out of programming code and put into normalized tables so that they are de-siloed and available to be shared enterprise-wide. Legacy systems should be included because even when they are replaced, conversion will be far easier when their files are normalized. Also, maintenance headaches from these systems will be greatly reduced.

Continuous normalization will move IT towards greater alignment to the organization's mission where IT can nimbly deliver new features and solve problems in the most efficient way.

http://www.gov-ideas.com/data_table_management.htm

http://www.gov-ideas.com/ea_implementation.htm

Cross agency data and process sharing opportunities, including, API, SOA and Web Services (Data Architect, IT and business side)

Is there a structured communication process with potential stakeholders available? Every potential integration point with other systems should be evaluated for loose vs. tight coupling, where any doubt is resolved in favor of loose coupling.

See super connector discussion for ideas on how to integrate government data with a phased approach.

Can an additional "organization_ID" field be added so that multiple agencies can concurrently use tables or programs as a centralized "cloud" application? (Executive office, CIO, Data Architect, IT and business side)

Beyond security and performance considerations, the additional code to make this application concurrently shared may not require much programmer effort.

The concept that enables the creation of cloud software is that only one extra field per database record is needed to make it sharable. For example, if an inventory system has these fields: item description, location and serial number, then all that's needed to make the table sharable for every government organization in the whole state is to add an organization_ID field to it. This is a simplification, but it gives the general idea. It keeps all of the data logically separate so that each governmental entity only sees data that pertains to it, but since all of the data is physically in one table, legislators, analysts and budget officials can obtain unfettered business intelligence from the database.

Cloud opportunities: Is there an business app cloud that this can become a part of? Should a business app cloud site be considered (statewide, nationally or for the general private business world)? See cloud discussion at
http://gov-ideas.com/cfgio.htm

Can this software system be obtained from (a) GOTS or (b) shareware sites? (Data architect, IT)

Can this software system be obtained from GOTS or shareware sites?

Can this software become (a) GOTS or (b) shareware? Make this available to all government as GOTS or maintain it at http://sourceforge.net/, a popular shareware site.

GOTS is the abbreviation for government off the shelf software.

Can any business processes be improved with existing data or be improved by changing the data model? Are there opportunities to re-engineer small, medium, or large, core, foundation business processes with new data models? (Data Architect, IT and business side)

For example, can processes that are paper-based bottlenecks be eliminated with already-existing data that should be integrated?

The purpose of this check is to ask if this is a good time to bring together the business process improvement side with the IT side to conduct performance reviews of, and consider reengineering, business processes. It is intended to encourage analysts to avoid assumptions and logic traps and instead to trace the chain of processes through layers of abstraction to determine if the organization's mission can be more optimally achieved.

Can this data be replaced by a better source of data elsewhere or replace other data? (Data Architect, IT, business side and federal or state CIO)

Can whole tables be eliminated by consolidation and sharing?

For example, if there is a list of government agency account numbers duplicated throughout state government, the redundant lists could be replaced by a link to a centralized list or receive automated downloads when the centralized one is updated. This would save manual editing work and reduce errors produced through manual updates.

Prioritize super connector fields and super connector tables. (Data Architect, IT and business side)

Super connector fields are those that cross agency boundaries.

Super connector tables are the most important tables that can be shared in-house and externally. These must be listed in a transparent, centralized database and reviewed for use whenever a new system is designed.

Vendor created systems must be reviewed for table/data sharing and naming conventions.

For more information on how to use super connectors, and a discussion on how to use data governance to create statewide and federal data integration, see the data governance article data-governance.htm

Can this data be used to validate other data or does it need validation performed on it? (Data Architect, IT and business side)

Business Intelligence - data mart/data warehouse opportunities (Business side)

Is there value to adding this to a data warehouse? Should a data warehouse be created if there is none? Can business clients be brought together to collectively discuss their requirements and justification for a data warehouse?

Can clients use the data to analyze business trends, discover fraud, or populate geospatial systems?

Are there informatics uses such as geoinformatics, criminal justice informatics, and business informatics?

Data harmonization problems or opportunities (Data Architect, IT and business side)

Semantic interoperability opportunities exist throughout all organizations, for example, "Distributed Cost" is called "Cost Allocation" elsewhere in the same organization. These terms should be unified and standardized enterprise wide to simplify business processes. Potential candidates are same words with different meanings, and different words with the same meaning.

Standards evaluation - Are there standards to be adhered to or created? (Data Architect, IT and business side)

Data standards, business standards, naming conventions, etc. For example, every state agency could have the same standard for this field: Corporation_Tax_ID_Number 40 characters - alphanumeric.

If data is exported externally, check to see if NIEM.gov already has a standard name for this field.

Are field, program and table names self-documenting and have consistent naming conventions?

Does this reveal the need for new standards which need to be created

Alignment to organizational mission. Strategic planning problems or opportunities (Data Architect, IT and business side)

Enterprise Architecture planning. How does it align with to the "To Be" architecture?

Impact on other systems (Data Architect, IT and business side)

Entered into dependency database (what systems does it impact or is it impacted by). This might include change control board system, ITIL, etc.

Metrics generation opportunities (business side)

Can this field or table create useful metrics or appear on a dashboard? Customers could include boards, licensees, the public, finance, governor's office and the legislature

Metadata opportunities (business side)

KPI - Key performance indicators opportunities (Data Architect, IT and business side)

Are there opportunities to use the field/table to measure performance?

Risk (Data Architect, IT and business side)

Can some data be put into production within strategically staggered time frames to reduce risk?

See risk-management-when-implementing-change.htm

Security (Data Architect, IT, business side and ISO)

Does the data require encryption, authentication, and authorization? Should backups be encrypted? What controls should be applied?

Should the security department review this matter?

Is data subject to legislative oversight or mandates? (Data Architect, business side)

E.g., Health Insurance Portability and Accountability Act (HIPAA), California Database Breach Act (California SB 1386), http://www.itl.nist.gov/fipspubs/geninfo.htm, FIPS, HSPD-12.

There needs to be a table of federal, state and departmental regulatory mandates or voluntary guidelines that reviewers check data against

Should clients be given control of the data? (Business side, IT)

Giving clients more control over their data, where feasible, often improves process efficiency.

Would a data steward be useful for this data? (Data Architect, IT and business side)

Backup considerations

How often should it be backed up? How does it get refreshed when there is a crash? When should it be purged? (IT and business side)

Can data quality be improved? Is data cleansing applicable? (IT and business side)

Why is the data not clean? Are there collaboration opportunities with outside agencies to validate the data?

Is data analyzed to identify when quality threshold or target levels are not being achieved?

Quality management (Data Architect, IT and business side)

Are clients satisfied? Is quality management and continual process improvement built into this system?

All data and software apps should have someone assigned to be
responsible for them. This is to avoid responsibility ambiguity.

There should also be a method for stakeholders to conveniently make
suggestions and contact responsible staff for all data and apps.
Convenience in making suggestions is a key factor in ensuring that
administrators receive feedback in a timely and consistent manner.

The responsible person for the data and apps would be assigned to:

  1. Create the suggestion method (suggestion box, suggestion email, online
    forum, etc.) and ensure that it is convenient to use
  2. Communicate to stakeholders the location or method for making
    suggestions and make the location or method easy to locate
  3. Review incoming suggestions and forward suggestions to appropriate
    staff responsible for improvements, and notify suggesters that
    suggestions were received
  4. Bring suggestions to a disposition and notify suggesters of the
    disposition (a) implemented (b) rejected (c) on back burner; waiting
    for analysis when more data or opportunities are available, etc.
  5. Every software application should have its own built in suggestion box
    on the application itself so that clients can intuitively use it to
    send suggestions directly to those responsible for the application at
    the time of use.

Suggestions should flow to into some centralized database for analysis
in order to discover overarching patterns and enterprise-wide
improvement opportunities.

Automated duplicate detection (IT)

Timeliness (IT and business side)

Is there value to the organization if the data is refreshed sooner or by other ways?

Is the data coming from the best sources (lineage; most reliable, timely)?

Review for entry into a table of future opportunities and linked to a calendar of related opportunities or future change events (Data Architect)

If a related component was scheduled for updating, that would trigger an automatic reminder to review opportunities for this component.

For example, assume two large systems have a data sharing opportunity but there is no budget for implementation. Add the opportunity to a "waiting list" of opportunities. In the future, when there is a work being done on the system that can include the task, or a budget is available to implement the opportunity, the data sharing can be realized.

Specify the priority on architect's data design waiting list. See data governance.

Optimization by combining multiple projects (past, future or ongoing projects) (Data Architect, business side, IT)

Are there other projects going on elsewhere in the state or federal government that would benefit from combining with this one?

Are there opportunities from making this available to a broader audience? (Data Architect, IT and business side)

Customers that are not immediately evident could include government boards, licensees, the public, police and investigative organizations, finance, governor's office, and the legislature

Audit policy - should the field or table be have its edit or use history recorded (IT and business side)

Error management. How should the system respond to the errors? E.g., should stakeholders or IT be notified if there are errors in the data? (IT and business side)

Are the business rules table-driven and controllable-by-clients where feasible? (Business rules should not be in programming code.) (IT, Data Architect)

Data tuning - is it fast enough? Is denormalization required? (IT)

Generally, data should be derived in real time when needed where feasible, however response time considerations denormalization and other techniques should be considered.

Field size and type - will the field be able to contain larger amounts of data 10 years from now? Are there auto alerts to notify clients and developers when files reach sizes large enough to overload the system? Are tables auto-tuned? Is it the right type of field (alphanumeric, numeric, etc.) (IT, Data Architect)

Note: this checklist is not a data dictionary.

Field and table added to data dictionary (IT, Data Architect)

Restartability (IT)

Have data and system been designed so that crashed programs restart without concern for partially filled data or partially completed processes? Has documentation been clearly communicated to clients and IT staff that there a no problems with process restarts?

Energy savings (Green unit, business side, IT)

Has the system designed to make default reports online instead of paper? Has server virtualization been considered, etc.?

Unstructured data links - Can HTML links be made to useful web sites at strategic places on the application? (Business side)

Web pages are unstructured data but may give consumers a richer information environment. Example, a government professional licensing application may contain physician license data for public verification. If the physician works for a corporation, a link to the state agency that licenses corporations where data regarding the corporation is located may give consumers a more integrated experience.

Does a new business process need to be created to improve data or add new data? Does a committee of business and IT members need to be created to analyze and implement the new business process to improve or create additional data? (Data Architect, IT and business side)

Transparency (Business side)

Can the system bring more transparency to the organization? How can more transparency be built into the system and the organization regarding any related business processes? http://sunlightfoundation.com , http://www.transparency.org, http://www.data.gov/about