The document discusses portfolio management of federal geospatial data assets according to OMB guidance. Portfolio management coordinates data assets and investments to efficiently support national priorities by reducing duplication, increasing accessibility, and enabling shared services across government. Datasets are organized into themes which are managed by theme leads and dataset managers using practices to improve data quality and access.
This presentation was from a joint BCS/DAMA event on 20/6/13 discussing different aspects of assessing data quality and the role that data quality dimensions can play.
This presentation by James Phare, Data to Value and Mark Hodson, X88 looks at the role that data profiling tools can play in assessing data quality.
The video for this presentation is at https://www.youtube.com/watch?v=XbSNw9gqoEo
Introduction to DCAM, the Data Management Capability Assessment Model - Editi...Element22
DCAM stands for Data management Capability Assessment Model. DCAM is a model to assess data management capabilities within the financial industry. It was created by the EDM Council in collaboration with over 100 financial institutions. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239. Also the benefits of DCAM are described as part of this presentation.
Akili offers an end to end approach to oil and gas upstream data management which includes: data strategy, governance, sustainability, Master Well Data Structure, system integration, system synchronization and data harmony.
Akili leverages best practices from PPDM (Professional Petroleum Data Management Group and applies our experiences leveraging the PPDM models with other companies.
Compliance issues can impact organizations in many ways. For medical device companies, this can be in the form of the FDA’s unique device identification (UDI) requirements. These requirements, a result of the passage of The FDA Amendments Act of 2007, stipulate that most medical devices carry a unique device identifier.
A webinar addressing how enterprise data management enables UDI compliance was presented live on May 23, 2013 in a joint session with Kelle O’Neal of First San Francisco Partners and Ross Hart of Riversand Technologies.
During the presentation, the following areas were discussed:
- The FDA legislation and the impact it will have on your organization
- Current UDI data challenges and benefits
- How enterprise information management and PIM support UDI
- How to get a UDI program started
- How to ensure a successful UDI program
These are the slides used in Kelle's portion of the presentation.
How Ally Financial Achieved Regulatory Compliance with the Data Management Ma...DATAVERSITY
A Data Management Maturity Model Case Study
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
Draft of Lesson 5
from the Course “Global Learning Framework” by Richard C. Close
For more information http://globallearningframework.ning.com
email: rclose@richardclose.info
Global Learning Framework is a trademark and copyright of Richard C Close All rights reserved
This presentation was from a joint BCS/DAMA event on 20/6/13 discussing different aspects of assessing data quality and the role that data quality dimensions can play.
This presentation by James Phare, Data to Value and Mark Hodson, X88 looks at the role that data profiling tools can play in assessing data quality.
The video for this presentation is at https://www.youtube.com/watch?v=XbSNw9gqoEo
Introduction to DCAM, the Data Management Capability Assessment Model - Editi...Element22
DCAM stands for Data management Capability Assessment Model. DCAM is a model to assess data management capabilities within the financial industry. It was created by the EDM Council in collaboration with over 100 financial institutions. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239. Also the benefits of DCAM are described as part of this presentation.
Akili offers an end to end approach to oil and gas upstream data management which includes: data strategy, governance, sustainability, Master Well Data Structure, system integration, system synchronization and data harmony.
Akili leverages best practices from PPDM (Professional Petroleum Data Management Group and applies our experiences leveraging the PPDM models with other companies.
Compliance issues can impact organizations in many ways. For medical device companies, this can be in the form of the FDA’s unique device identification (UDI) requirements. These requirements, a result of the passage of The FDA Amendments Act of 2007, stipulate that most medical devices carry a unique device identifier.
A webinar addressing how enterprise data management enables UDI compliance was presented live on May 23, 2013 in a joint session with Kelle O’Neal of First San Francisco Partners and Ross Hart of Riversand Technologies.
During the presentation, the following areas were discussed:
- The FDA legislation and the impact it will have on your organization
- Current UDI data challenges and benefits
- How enterprise information management and PIM support UDI
- How to get a UDI program started
- How to ensure a successful UDI program
These are the slides used in Kelle's portion of the presentation.
How Ally Financial Achieved Regulatory Compliance with the Data Management Ma...DATAVERSITY
A Data Management Maturity Model Case Study
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
Draft of Lesson 5
from the Course “Global Learning Framework” by Richard C. Close
For more information http://globallearningframework.ning.com
email: rclose@richardclose.info
Global Learning Framework is a trademark and copyright of Richard C Close All rights reserved
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...Enterprise Knowledge
Thomas Mitrevski, Senior Data Management and Governance Consultant and
Lulit Tesfaye, Partner and Vice President of Knowledge and Data Services
presented “Case Studies: Applications of Data Governance in the Enterprise” on December 6th, 2023 at DGIQ in Washington D.C.
In this presentation, Thomas and Lulit detailed their experiences developing strategies for multiple enterprise-scale data initiatives and provided an understanding of common data governance and maturity needs. Thomas and Lulit based their talk on real-world examples and case studies and provided the audience with examples of achieving buy-in to invest in governance tools and processes, as well as the expected return on investment (ROI).
Check out the presentation below to learn:
How Leading Organizations are Benchmarking Their Data Governance Maturity
Why End-User Training was Imperative in Seeing Scaled Governance Program Adoption
Which Tools and Frameworks were Critical in Getting Started with Data Governance
How Organizations Achieved Success with Data Governance in Under 12 Weeks
What Successful Data Governance Implementation Roadmaps Really Look Like
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Results from the FAIR Expert Group Stakeholder Consultation on the FAIR Data ...EOSCpilot .eu
Turning FAIR into Reality report and action plan by Simon Hodson, Executive Director of CODATA, delivered during the FAIR Data Session at the EOSC Stakeholders Forum 2018
Bridging Data Gaps with a Solid Data Foundation - A Key Imperative for Today’...Denodo
Watch full webinar here: https://bit.ly/3CjoaxS
In this session, the panel will discuss the importance of laying out a solid data foundation for everything digital for any financial institution. The panelists from UFCU and DevFacto will share their journey and agile approach toward data management in a hybrid data environment.
From this session, you will learn how UFCU gained unprecedented agility in data management and built the foundation for a “member 360” view. Devfacto worked with UFCU to design and set up multiple service streams. To streamline cloud adoption, and seamlessly unify cloud and on-premise data sources. Denodo’s Logical Data Platform enabled UFCU with reusable Lego-like building blocks to create different data views for business teams.
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:
- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities
Presentation given by Sarah Jones and Martin Donnelly outlining the UK RDM landscape, JISC MRD programmes, and DCC initiatives.
The presentation was given at Statistics New Zealand on 28th March, ANDS webinars on 29th & 30th March and Monash University on 2nd April 2012.
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...Enterprise Knowledge
Thomas Mitrevski, Senior Data Management and Governance Consultant and
Lulit Tesfaye, Partner and Vice President of Knowledge and Data Services
presented “Case Studies: Applications of Data Governance in the Enterprise” on December 6th, 2023 at DGIQ in Washington D.C.
In this presentation, Thomas and Lulit detailed their experiences developing strategies for multiple enterprise-scale data initiatives and provided an understanding of common data governance and maturity needs. Thomas and Lulit based their talk on real-world examples and case studies and provided the audience with examples of achieving buy-in to invest in governance tools and processes, as well as the expected return on investment (ROI).
Check out the presentation below to learn:
How Leading Organizations are Benchmarking Their Data Governance Maturity
Why End-User Training was Imperative in Seeing Scaled Governance Program Adoption
Which Tools and Frameworks were Critical in Getting Started with Data Governance
How Organizations Achieved Success with Data Governance in Under 12 Weeks
What Successful Data Governance Implementation Roadmaps Really Look Like
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Results from the FAIR Expert Group Stakeholder Consultation on the FAIR Data ...EOSCpilot .eu
Turning FAIR into Reality report and action plan by Simon Hodson, Executive Director of CODATA, delivered during the FAIR Data Session at the EOSC Stakeholders Forum 2018
Bridging Data Gaps with a Solid Data Foundation - A Key Imperative for Today’...Denodo
Watch full webinar here: https://bit.ly/3CjoaxS
In this session, the panel will discuss the importance of laying out a solid data foundation for everything digital for any financial institution. The panelists from UFCU and DevFacto will share their journey and agile approach toward data management in a hybrid data environment.
From this session, you will learn how UFCU gained unprecedented agility in data management and built the foundation for a “member 360” view. Devfacto worked with UFCU to design and set up multiple service streams. To streamline cloud adoption, and seamlessly unify cloud and on-premise data sources. Denodo’s Logical Data Platform enabled UFCU with reusable Lego-like building blocks to create different data views for business teams.
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:
- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities
Presentation given by Sarah Jones and Martin Donnelly outlining the UK RDM landscape, JISC MRD programmes, and DCC initiatives.
The presentation was given at Statistics New Zealand on 28th March, ANDS webinars on 29th & 30th March and Monash University on 2nd April 2012.
Similar to 2013 05-01-portfolio-management-at-a-glance-sheets (20)
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
Top mailing list providers in the USA.pptxJeremyPeirce1
Discover the top mailing list providers in the USA, offering targeted lists, segmentation, and analytics to optimize your marketing campaigns and drive engagement.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
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As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
Building Your Employer Brand with Social MediaLuanWise
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In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
1. Portfolio Management, according
to Office of Management and
Budget (OMB) Circular A-16
Supplemental Guidance, is the
coordination of Federal geospatial
data assets and investments to
most efficiently support national
priorities and government
missions.
Portfolio Management applies
consistent management
approaches that help increase the
quality of data through best
practices and documentation in a
manner that:
reduces duplication and cost
provides greater accessibility
supports shared services
across the Federal
Government
Better
Management
Better
Outcomes
Approach Outcomes
Better
understanding
of available
data
Increased
information
sharing
More informed
decision
making
Reduced
duplication of
effort
Improved
transparency
in investment
activities
Coordinated
delivery of
common
geospatial
services
Datasets are organized into management units called Themes which are managed
by Theme Leads. Dataset Managers and Theme Leads use industry accepted
practices to improve management of Datasets and Themes leading to better
outcomes. Data within Themes are made available through the Geospatial Platform
(www.geoplatform.gov).
How does Portfolio Management work?
Portfolio
Theme
Dataset Dataset Dataset
Theme
Dataset Dataset
Portfolio Management
Ensuring the Quality of National Geospatial Assets
PortfolioManagement–Overview
2. National Geospatial Data Asset (NGDA) Themes are organizational constructs
under which Datasets are grouped and managed. The 16 Themes are:
• Biota
• Cadastre
• Climate and Weather
• Cultural Resources
• Elevation
• Geodetic Control
• Geology
• Governmental Units, and
Administrative and
Statistical Boundaries
• Imagery
• Land Use-Land Cover
• Real Property
• Soils
• Transportation
• Utilities
• Water – Inland
• Water – Oceans & Coasts
Who manages the Datasets and Themes?
Dataset Managers provide information to their Theme Lead for
management and reporting.
For more information go to
www.FGDC.gov/PortfolioManagement
What will the Portfolio ultimately consist of?
What are NGDA Themes?
Dataset Manager provide
coordination and standards
for Datasets at a national
level. Dataset Managers
use the Geospatial Data
Lifecycle to manage their
Datasets.
Dataset Managers
Theme Leads provide cross-
agency leadership and
coordination for the Theme.
Theme leads will submit Theme
reports to the FGDC.
Theme Leads
Here is an example of how a Theme within the
Portfolio will be set up.
PortfolioManagement–Overview
National
Watershed
Dataset
Water Theme
National
Wetlands
Dataset
National
Hydrography
Dataset
NGDA Portfolio
4. The NGDA Portfolio Management Process
The Portfolio Management Process
The Portfolio Management Process includes an annual
review of assets, consistent management of current data,
and annual progress reporting.
Inventory – Identify existing geospatial datasets that may be considered National
Geospatial Data Assets (NGDAs). The FGDC Steering Committee must know what
geospatial data exist and how they support the business requirements of the Federal
Government and its partners.
Select – Determine if the datasets are NGDA Datasets and if they should become
part of the Portfolio. Inclusion will be based on the following criteria for individual
Datasets:
• Used by multiple agencies and partners;
• Needed to support Presidential priorities as expressed by OMB;
• Required to meet shared mission goals of multiple Federal agencies; or
• Expressly required by statutory mandates.
Manage – Develop and manage Datasets per the OMB Circular A-16 Supplemental
Guidance. This phase of consists of activities at both the Theme and Dataset levels.
These include an initial baseline assessment, implementation of the data lifecycle,
and preparation of an annual Portfolio Summary Report.
Evaluate/ Monitor – Develop Dataset, Theme, and Portfolio summary reports that
capture plans, milestones, and progress of the Portfolio. Metrics will provide a
comprehensive picture of the Portfolio allowing better enterprise-level decision-
making
Identify and Execute – Develop NGDA Theme and NGDA Dataset improvement,
funding, and priorities. Annual recommendations are made on Portfolio actions.
Inventory Select Manage
Evaluate /
Monitor
Identify &
Execute
A key goal of Portfolio Management is to enable the FGDC Steering Committee to
make informed decisions on setting both short- and long-term priorities on Themes
and Datasets as well as cross-agency collaboration targets for Dataset development
and funding.
PortfolioManagement–Process
5. The Key Roles within Portfolio Management
Theme Leads are responsible for the coordination and integration of multiple
Datasets that are often managed in separate agencies. Theme Leads coordinate
with their respective Dataset Managers to provide overall management for the
Datasets associated with the Theme. This will ensure that all relevant Datasets
associated with a particular Theme effectively support the business processes reliant
on them; and that they are produced in the most cost effective manner. Each Theme
Lead also coordinates with other Theme Leads to ensure that Datasets applicable to
more than one Theme are effectively co-developed. In short, Theme Leads are the
master coordinators that guide the overall Portfolio Management process.
Dataset Managers use the Geospatial Data Lifecycle to plan, develop, maintain,
evolve, and archive the NGDA Dataset(s) for which they are responsible. They will
also use the Geospatial Data Lifecycle and the associated evaluation criteria to
provide Dataset reports to the Theme Lead.
The Theme Leads compile Dataset reports to look across the Theme and identify
potential coordination opportunities, efficiencies, and investment and development
priorities. These outputs are communicated to the FGDC for consideration in annual
investment planning.
For more information go to
www.FGDC.gov/PortfolioManagement
PortfolioManagement–Process
7. Stage 1. Define: Characterization of data requirements based upon business-driven
user needs.
Stage 2. Inventory/Evaluate: Creation and publication of a detailed list of data
assets and data gaps (both internal and external) as they relate to business-driven
user needs.
Stage 3. Obtain: Identify the mechanism(s) for the collection, purchase, conversion,
transformation, sharing, exchanging, or creation of geospatial data that were
selected to meet the business needs.
Stage 4. Access: Making data produced known and retrievable to the community
through documentation and discovery mechanisms so the users can meet their
business requirements.
Stage 5. Maintain: Ongoing processes and procedures for data operation and
maintenance to ensure that the data continue to meet business requirements.
Stage 6. Use/Evaluate: Ongoing assessment, validation, and potential
enhancement of data to meet user needs and business requirements.
Stage 7. Archive: Required retention of data and the data’s retirement into long-
term storage.
Outcomes
• Better understanding of Dataset
quality
• Identification of best management
practices
• Availability of geospatial data to
support business processes and
operations
• Strengthens partnerships and
coordination across all levels of
government to increase cost
efficiency and return on investment
• Improved efficiencies in
addressing Federal and national
priorities, and enhancing citizen
service
Define
Inventory
/ Evaluate
Obtain
AccessMaintain
Use/
Evaluate
Archive
Geospatial
Data
Lifecycle
The Dataset Management Process
The Geospatial Data Lifecycle is the management approach
adopted by Federal agencies to ensure the quality and reliability of
National Geographic Data Assets (NGDA) Datasets.
PortfolioManagement–Datasets
8. Requirements for Managing Data
For more information go to
www.FGDC.gov/PortfolioManagement
PortfolioManagement–Datasets
Dataset Managers implement the Geospatial Data Lifecycle to ensure
that data are trustworthy and useful and that data going to the
Geospatial Platform are current and reliable. Additionally, Dataset
Managers submit annual reports on their Datasets to their respective
Theme Lead.
Theme
Lead
Dataset
Manager
Dataset
Manager
Dataset
Manager
Annual reports
Dataset Management involves implementing the Geospatial Data
Lifecycle, promoting the maturity of Datasets, monitoring key
indicators for annual dataset reports, and providing status
of performance measures.
Regular evaluation of
Datasets, through
annual dataset reports
and Thematic
Subcommittee
discussions, will
ensure that Datasets
are current and
relevant.