Statewide Data Governance Assessment
Current Data Systems, Governance Structures, and Data Management Protocols Across New Mexico State Government
Executive Summary
The New Mexico Legislature appropriated funding in 2024 for the Institute for Complex Additive Systems Analysis (ICASA) at the New Mexico Institute of Mining and Technology to analyze New Mexico’s current data systems, data governance structures, and data management protocols. This project responds to the increasing need for secure, coordinated, and effective data governance across state government to improve decision-making, strengthen public services, and protect sensitive information.
To fulfill this legislative directive, ICASA conducted a mixed-methods assessment that included interviews with New Mexico agency leaders, discussions with national Chief Data Officers and subject matter experts, stakeholder engagement sessions, qualitative surveys, and research into existing state statutes, administrative rules, and best practices. The project also supported criminal justice data governance initiatives through collaboration with the New Mexico Sentencing Commission and efforts to reestablish the Justice Information Sharing Council (JISC).
- Evidence of state-wide data governance advances
- Inconsistencies in capacity, staffing, standards, and practices
- Need for direction and state-wide standards/collaboration
- Building trust in and demonstrating value of data governance is essential
- Recommend establishment of Chief Data Office
The assessment found that New Mexico possesses numerous strengths upon which to build a statewide data governance framework. Many agencies have developed sophisticated data systems, formal governance processes, and successful data-sharing initiatives. Significant investments in systems such as SHARE, RiseNM, health information exchanges, criminal justice data platforms, and agency-specific governance models demonstrate that meaningful progress has already occurred across state government.
However, the assessment also identified significant inconsistencies across agencies. Technology capacity, staffing, governance maturity, data standards, interoperability, and formal data-sharing practices vary considerably. Many agencies continue to rely on legacy systems, limited technical resources, or informal governance processes that constrain collaboration and increase operational risk. The absence of enterprise-wide standards, comprehensive system inventories, and consistent governance policies limits New Mexico’s ability to maximize the value of its public data assets.
Interviews with Chief Data Officers from other states consistently emphasized several lessons applicable to New Mexico. Successful statewide governance initiatives are built through collaboration, trust, incremental implementation, and demonstrated value rather than solely through regulatory mandates. States with mature governance programs have established clear executive leadership, defined agency responsibilities, invested in data stewardship, and created sustainable mechanisms for cross-agency coordination.
The criminal justice stakeholder convening reinforced many of these findings. Participants identified trust, common data standards, stronger communication, sustainable governance structures, and continued technical assistance as essential components of successful statewide collaboration. Stakeholders also emphasized that the ultimate objective of data governance is not governance itself, but enabling secure access to reliable information that supports informed policy decisions and improved public outcomes.
Based on these findings, this report recommends the development of a statewide data governance strategy centered on transparency, security, interoperability, accountability, and equitable access to data resources. Key recommendations include establishing an enterprise Chief Data Officer, designating agency-level data stewards, modernizing legacy technology, strengthening statewide governance standards, expanding data literacy and workforce development, increasing cross-agency collaboration, leveraging federal funding opportunities, and institutionalizing regular statewide governance forums.
“Ultimately, data governance is not an end in itself. Its purpose is to enable secure, responsible, and effective use of information that supports better public policy, improves government operations, enhances transparency, protects privacy, and delivers better outcomes for the people of New Mexico.”
New Mexico has an opportunity to build upon existing agency successes and create a coordinated statewide framework that enables secure data sharing, strengthens public trust, improves operational efficiency, and supports evidence-based policymaking. By adopting a phased and collaborative approach informed by national best practices, the State can position itself to meet the growing demands of modern government while protecting the privacy and security of the information entrusted to it.
The Report
Introduction
The Institute for Complex Additive Systems Analysis (ICASA) was created in 2001 through enabling legislation by the State of New Mexico (§21-11- 8.1). A research division of the New Mexico Institute of Mining and Technology, ICASA’s mission is to advance the research, development, and science of critical infrastructure protection. That means training, equipping, and deploying a generation of critical thinkers to help solve the complex problems facing a connected and data-rich world.
Leveraging “state support” is essential for this effort, enabling ICASA to apply knowledge gained through joint projects to discover and develop new analytics for noisy, incomplete data using cross-domain datasets and collaboration.
The U.S. Government and the State of New Mexico sponsored the creation of ICASA at New Mexico Tech in the late 1990s in response to the U.S. Department of Defense (DoD) and the U.S. Intelligence Community’s growing recognition of the need to model, analyze, and manage the growing complexity of infrastructure vulnerability analysis and protection, information assurance, and information warfare.
ICASA has demonstrated numerous proofs of concept for the evolving, complex systems that represent the U.S. Critical Information Infrastructure. ICASA has pioneered new forms of personnel education and training, both internally and at its customer sites, in the interdisciplinary, creative-thinking processes usually neglected in traditional educational programs. As a result, ICASA has enabled its customers to assess the vulnerabilities of virtually any evolving complex infrastructure effectively.
New Mexico Institute of Mining and Technology has been designated by both the National Security Agency and the U.S. Department of Homeland Security as a National Center of Academic Excellence in Information Assurance Education and Assurance Research. Most ICASA professional staff, faculty, and student researchers hold security clearances necessary to meet Federal Government requirements. Since 2001, ICASA has directly supported issues of interest to the U.S. Intelligence Community and other DoD and DoE agencies. More recently (FY18 to present), ICASA has supported several New Mexico Criminal Justice-focused organizations with data aggregation and analysis efforts using data science to address public-interest problems.
Research Methodology
The findings presented in this report are based on a mixed-methods research approach designed to provide a comprehensive assessment of New Mexico’s current data governance environment while identifying opportunities for future statewide coordination.
The research methodology was reviewed and approved by the New Mexico Institute of Mining and Technology Institutional Review Board (IRB) and consisted of the following components.
Legislative Review
- Review of the 2024 legislative appropriation establishing the project
- Review of relevant New Mexico statutes, administrative rules, executive directives, and agency guidance
- Review of applicable federal privacy and security requirements, including HIPAA, FERPA, CJIS, and related federal standards
Agency Research
- Assessment of executive branch agencies, including:
- Data systems and technology platforms
- Governance structures
- Data management protocols
- Staffing and organizational capacity
- Data-sharing practices
- Technology modernization initiatives
Stakeholder Engagement
Project staff conducted individual interviews, small-group discussions, and stakeholder meetings with representatives from: - Executive agencies - Quasi-public organizations - Criminal justice agencies - Education agencies - Health and human services organizations - Information technology leaders
National Comparative Analysis
Interviews were conducted with Chief Data Officers and statewide data governance leaders from multiple states to identify successful governance models, implementation strategies, and lessons learned that may inform New Mexico’s future efforts.
Criminal Justice Convening
ICASA partnered with the New Mexico Sentencing Commission to convene criminal justice stakeholders representing state agencies, local governments, academia, and national experts to discuss opportunities for improving statewide data governance and collaboration.
Open-Source Research
The assessment incorporated publicly available information regarding: - State agency technology systems - National data governance frameworks - Published reports - Academic literature - Government best practices - Existing statewide initiatives
Project Goal
The purpose of this assessment is to provide policymakers with an objective overview of New Mexico’s current data governance landscape while identifying practical opportunities to strengthen statewide collaboration, improve data stewardship, modernize technology infrastructure, and support evidence-based decision-making.
Project Background
The New Mexico State Legislature funded the Statewide Data Governance Project through a 2024 Legislative appropriation in HB 2, specifically: “to analyze and report on current data systems, data governance structures, and data management protocols.” The project provides legislators and key stakeholders with a report on New Mexico’s existing data governance structures, data-sharing mechanisms, and systems across intergovernmental and quasi-public-sector agencies. Secondly, this project engages stakeholders through individual conversations, small-group discussions, and data governance stakeholder meetings. The third component focuses on supporting data governance improvement efforts in the criminal justice system through its work with the New Mexico Sentencing Commission, which includes supporting efforts to re-establish the Justice Information Sharing Council (JISC)
Project Components
Report to the Legislative Finance Committee
The following report is based on findings from a mixed-methods research approach approved by New Mexico Tech’s Institutional Review Board. The methodology includes stakeholder engagement, state-based expert interviews, national data governance expert interviews, qualitative surveys, and open-source research. The report, contents below, include the following: - New Mexico’s Public Sector Data Systems and Structures (software, data entry/sharing/utilization systems, relevant data governance legislation, New Mexico Administrative Code citations, etc.) - Data governance structures - Data management protocols - Data capacity - Data governance policies, rules, and regulations - Data Governance Learnings from Other States - Strengthening New Mexico’s Data Governance Infrastructure: Recommendations
Criminal Justice Stakeholder Engagement
The purpose of convening New Mexico’s criminal justice stakeholders was to create a neutral and trusted environment for data leaders and stakeholders to discuss data-sharing practices and data management protocols, identify shared focus areas, and explore opportunities for collaboration. The convening aimed to support the project’s broader goal of strengthening the state’s data governance infrastructure.
Specific Goals: - Secure stakeholder buy-in for long-term collaboration and data-sharing. - Gather valuable insights into data governance across sectors to inform ICASA’s report to the Legislative Finance Committee. - (Internal goal) Elevate ICASA’s visibility and credibility within the data governance space.
Attendees: a focused group of 20–30 key stakeholders that include
middle management and leadership from public and quasi-public sector agencies,
external guests (e.g., academic experts, Chief Data Officers (CDOs) from other states), and
experts from New Mexico state agencies with relevant domain knowledge. Below is an overview of the stakeholder meeting:
New Mexico Sentencing Commission Collaboration
ICASA’s data governance staff is working with NMSC to reestablish the Justice Information Sharing Council (JISC), an advisory body established by the New Mexico Sentencing Commission (NMSC) to enhance collaboration and data sharing across New Mexico’s criminal justice agencies and systems. The Council will be critical in improving data-driven decision-making within the justice system. ICASA data governance staff provide strategic guidance, administrative support, and technical assistance as needed. It is an opportunity to demonstrate, in a practical setting, the importance of strong data governance and its benefits for a public policy ecosystem.
Context: Comparing State Perspectives on Data Governance
- It is vital to build trust by listening to agencies before formalizing policy or structure
- Building belief in data governance requires ongoing incremental benefits to “business side”
- “Delivery arm” enhances agency capacity and builds positive sentiments about data governance
- Punitive data policies can backfire and reduce agency buy-in
- Matching data governance funding with mandates and small grant opportunities essential for success
To inform the development of New Mexico’s statewide data governance framework, interviews were conducted with Chief Data Officers (CDOs) from Colorado, Connecticut, Montana, Maine, North Dakota, and Wyoming, among others. These discussions provide practical insights into governance design, organizational structure, political authority, implementation sequencing, and change management. While each state operates within a distinct statutory and political context, several consistent themes emerged that are directly relevant to New Mexico’s policy deliberations.
Many interviewees emphasized the importance of sequencing implementation carefully. Montana’s CDO described taking a deliberate “pull” approach, prioritizing listening sessions with agency leadership before formalizing structure or policy. This strategy recognized that data governance can be perceived as process-heavy and restrictive, particularly in state environments that already operate under significant procedural requirements. Building credibility through early collaboration proved essential.
Maine’s experience illustrates a complementary perspective. Although the initiative was supported by executive leadership and equity-focused mandates, the CDO emphasized that formal authority alone does not eliminate resistance. Resource limitations, agency hesitancy, and unclear enforcement mechanisms remain substantial challenges. Maine’s leadership reflected that beginning with narrower, highly achievable initiatives—such as focused data cataloging tied to critical business processes—may have accelerated buy-in.
Multiple states underscored the importance of early, demonstrable wins. Montana concentrated on small, fundable projects capable of producing measurable return on investment, using those successes to build cross-agency momentum. Demonstration through recurring data summits and interagency forums gradually increased enterprise data literacy and normalized governance practices.
Colorado’s CDO emphasized the importance of a “delivery arm.” Producing demonstrable data governance solutions for agencies was key in their state’s ongoing success. A former CDO from North Dakota described it as changing the perception of data governance from “I’m not going to get my data” to a process that enhances the ability of state agencies to operate.
Organizational placement of the CDO role also emerged as a significant factor. Maine’s and Connecticut’s experiences suggest that situating the CDO parallel to, rather than subordinate to, the CIO can reinforce that governance is an enterprise business function rather than solely a technical initiative. Clear statutory authority and defined enforcement mechanisms further strengthen implementation capacity.
Washington’s CDO warned, however, that regulatory “teeth” can backfire. Many agencies may do only enough to be minimally compliant in order to avoid punishment, eschewing more substantial commitments to advance public data governance. Colorado’s former CDO reiterated this point, arguing that trust very often achieves more than punitive policies can, especially when agencies think that the latter could potentially disappear after a change of administration.
Finally, many states highlighted the importance of aligning scope with fiscal reality. Montana structured a small, highly capable central team focused on advisory oversight and best-practice guidance rather than direct operational control. Complementing this model with clearly identified agency-level data owners and stewards supports distributed accountability while maintaining enterprise standards.
Yet, the structure of funding mechanisms appeared to be as important as the amount available within state budgets. Many CDOs expressed frustration with the tendency for funding to go toward periodic, multi-million dollar “boil the ocean” projects, when many agencies instead need more consistent support to modernize their data governance and/or the ability to access funding for shorter-term projects.
At the same time, as Colorado’s former CDO put it, most agencies don’t explicitly go out looking to buy data governance. They want to fund their operations. However, data governance is increasingly essential to delivering value to citizens. Adequately supporting ongoing data governance development may require viewing it as akin to IT, as essential infrastructure undergirding the day-to-day operations of state agencies.
Assessment of New Mexico’s Current Data Governance Infrastructure
- Stark unevenness in technical capacity, personnel, and data governance maturity level
- Agencies struggle with data fragmentation and inconsistent data entry
- State risk profile includes those derived from vendor-provided and internally maintained data systems
- Informal and unreported data sharing agreements very likely exist
- Battling inconsistencies requires state leadership in defining minimum governance controls across agencies
New Mexico’s executive-branch agencies have a non-uniform model of data and technology capacities, systems, and governance practices that vary widely across missions, staffing levels, and vendor dependence. The spreadsheet, shared as supplemental material, provides a cross-agency snapshot of whether agencies report dedicated data and technology personnel, approximate staffing levels, the named lead point of contact (often a CIO or equivalent), the primary data management software/system in use, whether a vendor supports that system, and whether agencies share data externally and have agreements in place. The unevenness of New Mexico’s data governance infrastructure results from notable strengths in certain areas as well as systemic gaps that constrain statewide interoperability, transparency, and consistent risk management.
Agency Attributes Based on Survey Results
The following spider charts characterize three select agencies with regard to their maturity level in multiple dimensions of data governance, such as in resources, the existence of a data governance council, etc.
New Mexico Environment Department
Department of Workforce Solutions
Public Education Department
Most of the 37 listed agencies report having data and technology personnel (31 agencies marked “Yes”), while a smaller subset report no dedicated data and technology personnel (6 agencies marked “No”). Agencies lacking internal technical capacity include the Indian Affairs Department, the Martin Luther King, Jr. State Commission, the New Mexico Medical Board, the Office of African American Affairs, the Office of the Governor, and the Office of the Lieutenant Governor.
These entities are more likely to rely on informal support arrangements, shared services, or ad hoc procurement—conditions that can heighten operational risk, slow service-delivery improvements, and complicate compliance with security and privacy requirements. The distribution of agency staffing is highly uneven. Reported staffing ranges from very small teams (as low as 1) to very large centralized capacity (up to 132). The median level is 12 persons, indicating that typical agency capacity is modest even when a dedicated function exists.
Agencies with enterprise-scale roles or large operational footprints, including the Department of Information Technology (132) and the Department of Health (93); several other large agencies report the largest staffing levels (40-60). This skew suggests that statewide modernization and governance initiatives are likely to rely disproportionately on a small number of higher-capacity agencies unless the state invests in lifting baseline capability across agencies.
The data management software/system field indicates substantial fragmentation. Many entries are unique, multi-system descriptions, while numerous agencies are coded as “Unknown” due to blank entries or insufficient detail. Some entries reflect transition environments or placeholders. This pattern is important for policy: fragmentation and incomplete system inventory impede statewide data governance because effective governance presupposes a known system landscape, consistent metadata, and clear system ownership and stewardship.
Vendor involvement is reported inconsistently. Some agencies explicitly indicate using a vendor for data management, others indicate no vendor, and many are coded as unknown or unclear. Vendors provide stability and specialized support but may also introduce risks related to cost escalation, contract lock-in, data portability, and uneven security accountability. Conversely, internally maintained systems may offer flexibility but are fragile to staffing changes. The dataset suggests New Mexico’s environment likely includes all of these risk profiles simultaneously, increasing the importance of centralized contract standards, shared cybersecurity baselines, and interoperability requirements embedded in procurement.
Seventeen agencies explicitly report sharing data with other state agencies or relevant entities, and in each of those cases, the spreadsheet indicates a data-sharing agreement is in place. The dataset references the HHS MMISR Project multiple times as a purpose for data sharing, indicating that a major modernization or integration effort in health and human services is driving formal data exchange practices across participating agencies.
“In summary, the spreadsheet depicts a state enterprise with meaningful pockets of maturity but significant inconsistencies in capacity, system documentation, and data-flow visibility.”
However, many agencies are coded as unknown for both data sharing and agreements. In a state government setting, it is unlikely that only the identified agencies share data; rather, it is more plausible that sharing is not consistently tracked, that informal exchanges exist outside formal agreement frameworks, or that the survey instrument did not capture the full range of exchanges. From a governance standpoint, the most significant signal is the breadth of uncertainty, which suggests the state cannot currently attest, at enterprise scale, to where sensitive data moves, under what authority, with what safeguards, and with what accountability.
Taken together, the spreadsheet points to a statewide governance opportunity focused on baseline standardization, inventory, and shared capability. Legislative priorities could include establishing an enterprise data and systems inventory requirement; defining minimum governance controls for data sharing; building shared services for low capacity agencies; embedding interoperability and data portability into procurement standards; and strengthening statewide accountability roles.
In summary, the spreadsheet depicts a state enterprise with meaningful pockets of maturity but significant inconsistencies in capacity, system documentation, and data-flow visibility. For legislative decision-making, the strongest policy signal is the need to move from agency-by-agency practices to a statewide governance baseline that ensures reliability, security, interoperability, and transparency
Criminal Justice Convening: High-level Takeaways
Below are key takeaways and learnings from the December 2025 Criminal Justice Stakeholder meeting ICASA co-hosted with the New Mexico Sentencing Commission.
Notable Meeting Themes
- Data governance is not the end goal; the goal is to have access to data so we can make informed decisions with data.
- Accessible data can help answer questions about outcomes for criminal justice, government officials, and much more.
- Data protection can sometimes hurt those whom they are trying to protect.
Changes in Data Governance in the Past Decade
- There is better decision-making being made due to better access to data.
- ICASA helps teams break through restrictions on data and allows the facilitation of data that is already public.
Data Governance Infrastructure: Strengths and Assets
- There is significant data already in the criminal justice realm; dashboards are needed to help communities.
- There is a need for more outside stakeholders to have access to data.
- There is a need for more face-to-face communication among stakeholders.
- There are many opportunities to use data for policy, program, and budget decisions. Accessible data is critical to helping the sector achieve more.
- ICASA can provide technical expertise that agencies do not have and are unable to fund.
- ICASA is neutral and can act as a mediator/facilitator for data interaction when agencies have different goals but require the use and sharing of the data.
- ICASA is successful as they are an outsider to many interpersonal issues. They can bypass these issues and work with relationships that have already been established with ICASA due to the variety of DSPI projects.
Barriers to Data Collaboration
- There are organizations with a lack of staff/resources, which hinders them to help with data sharing and prioritize data.
- Agencies need disposition codes that are understandable. There is a lack of common definitions across the state. (Coordination)
- Many silos still exist within the criminal justice ecosystem.
- There is a lot of growth internally that needs to be done. (Silos within Silos)
- Agencies have issues with people requesting data that they do not need.
- Safe data can be released to the public so that requests do not clog systems.
- Data governance policy implications are often viewed as policies that will result in a lot of work and no return on investment.
- There are many technical capabilities available. Why not take advantage of them?
- Collecting data in an appropriate manner will allow agencies to keep track of information without being at risk of losing it.
In-State Data Governance Needs
- Looking at data coming in and out to build effective governance (cataloging data).
- The same data can be used from areas such as DOC, Court Records, Jail Records, etc. This will help avoid conflict due to CJIS violations.
- The key north star of data governance is “trust.” Systems need to be put in place so there is trust that the data will be protected when shared.
- Data Governance requires frameworks that need to be built piece by piece for better implementation and to address data quality issues.
- Larger counties have an easier time-sharing data, whereas smaller counties find it more difficult, as they have outdated systems/databases. (Up-to-date technology)
- Smaller counties are dealing with limited budgets and small amounts given by the state. (Systems are not compatible)
- Changes in technology need to be shared so that relevant information continues to be shared between agencies.
Institutionalize Data to Outlive Worker Tenures
- Give clear expectations on what needs to be done with data and how it should be structured. Make a repository that asks users who are sending data to comply with the standard.
- More Data Governance team meetings to discuss issues and build chemistry.
- Data Governance policies cannot be a majority vote; it must be unanimous, with everyone believing in it.
- Make data governance a priority in the different levels of government, public, and individual organizations.
Reasons to Invest in High Quality Systems
- Some agencies DO NOT have the database systems that allow for sharing and engagement (analyses) with the data.
- A common language can be developed for all agencies. Educating the public will require the use of a common language.
- ICASA is a technical wing and could help agencies do their jobs better. (System that supports agencies equally)
- Data could be one of New Mexico’s biggest public assets.
- Some companies that built data systems are controlling conversations about data governance.
- ICASA can put tools in place that limit the access each agency has to it, depending on what is relevant to the respective agency.
What Agencies Can Do Now
- Attack the problems that need to be solved and discussed within the agency. Attend data governance meetings and share challenges.
- Talk to leaders of agencies to get on board in prioritizing how data operations can be improved.
- Understand the data you own in your agency and the restrictions that are put on that data.
- Build relationships by working with other agencies and discussing similar issues involving data sharing
New Mexico’s Data Governance Infrastructure Challenges
Despite the availability of tools, systems, and protocols, New Mexico faces several challenges and opportunities to strengthen its data governance infrastructure.
Interoperability Issues: Some legacy systems in state agencies are not fully interoperable with newer platforms, limiting the efficient data exchange across different agencies.
Privacy Concerns: As the state manages and shares vast amounts of sensitive data, such as health and criminal justice records, there are heightened concerns regarding privacy breaches.
Resource Limitations: Budget constraints often limit agencies’ ability to invest in state-of-the-art data-sharing technologies and staff training, impacting the scalability and efficiency of data-governance initiatives.
“End-User” Development: Many agency staff members welcome the opportunity to collaborate in data governance, rather than feel steered by outside vendors.
More Robust Management Protocols: Limited data management protocols exist for data collaboration, sharing, and utilization, making it challenging for agencies to exchange data.
Data is Siloed by Issue Area: Issue-based data collaboration efforts are siloed within a policy area, making it challenging for agencies and decision-makers across New Mexico’s state government to have a complete picture outside of that policy area.
Recommendations
Develop a Statewide Data Governance Strategy
What is the vision for data governance in New Mexico? New Mexico’s “North Star” for data governance could be to build a state-wide, integrated, and secure data infrastructure that supports efficient and transparent data sharing across all agencies. This infrastructure includes a blueprint of the existing data systems, how they interface, a culture that prioritizes data governance, and the management protocols in place to protect the data and enable sharing, as appropriate. This would provide New Mexico decision-makers with the tools and access to data to make more data-driven decisions, improve public services, and maintain the highest privacy and security standards.
Core Values/Principles:
Transparency: Public access to non-sensitive data to foster accountability.
Efficiency: Streamlined, real-time data sharing across agencies to enable timely decision-making.
Security: Robust safeguards that protect sensitive information and ensure compliance with privacy regulations.
Equity: Ensuring that all state employees, regardless of agency, have the capacity and tools to manage data effectively.
Control: Ensuring that all agencies can see who is using their data and have the capacity to identify and address the misuse of data.
Opportunities to help New Mexico realize this vision:
Technology Modernization: Upgrading legacy systems to more flexible, cloud-based platforms would enhance data-sharing capabilities.
Enhancing Data Privacy and Security: Ensure all policies and protocols go beyond standard rules and compliance requirements. This is important to mitigate the risk of information breaches or unintended data misuse due to personnel turnover, inexperience, and/or urgency, which can lead to improper handling and sharing of data.
Cross-Agency and Interstate Collaboration: Encourage greater collaboration among state agencies by establishing regular crossagency data-sharing opportunities and by developing or leveraging existing working groups to identify gaps in current protocols and systems.
Encourage cross-agency working groups to regularly assess and improve data-sharing practices.
Increase collaboration with other states to adopt best practices and modern frameworks.
Enhancing Data Literacy: Training and Capacity Building
Develop statewide data literacy, management protocols, and training programs to equip employees with the skills needed to manage and secure data.
Implement data stewardship roles within each agency to maintain quality control over shared data.
Leverage Federal Resources: Tap into federal grants and resources to improve state data infrastructure
Expand Open Data Initiatives: Continue to promote sharing nonsensitive public data through portals, ensuring transparency while safeguarding sensitive information.
Partnerships with Other States: Partner with states leading on data governance to learn from their successful data governance strategies and share knowledge.
Legislative Opportunities
Based on comparative state experience, the Legislature may wish to consider the following actions to strengthen New Mexico’s data governance framework: