19
Statistical and Spatial Frameworks, Standards and Data Infrastructure Work Session on Statistical Metadata 2013 WP11 Alistair Hamilton [email protected]

Statistical and Spatial Frameworks, Standards and Data Infrastructure

  • Upload
    saddam

  • View
    58

  • Download
    0

Embed Size (px)

DESCRIPTION

Statistical and Spatial Frameworks, Standards and Data Infrastructure Work Session on Statistical Metadata 2013 WP11 Alistair Hamilton [email protected] Australian Bureau of Statistics (ABS). Content Space is big…and getting bigger - PowerPoint PPT Presentation

Citation preview

Page 1: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Statistical and Spatial Frameworks,

Standards and Data Infrastructure

Work Session on Statistical Metadata 2013WP11

Alistair [email protected] Bureau of Statistics (ABS)

Page 2: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Content

1. Space is big…and getting bigger

2. The emergence of spatial data & metadata standards

3. Global Geospatial Information Management (GGIM) Initiative and UNSC Programme Review

4. Toward an international statistical geospatial framework.

5. A national example from Australia

6. Conclusions, and possible topics for consideration

Page 3: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Space : The universal frontier• Space and time are the framework within which the mind is

constrained to construct its experience of reality• Immanuel Kant• Statistics has traditional focused more on time series analysis than spatial

analysis?

• Connecting information with space assists in connecting it with experienced reality• Location – experience of place (point)• Experience of movement through (or connection across) space (line)• Spatial extent – experience of domain (polygon)

• Eg neighbourhood, boundaries of countries , service (and sales) regions

• Along with official statistics, geospatial information is an indispensable element in the information system of a democratic society

Page 4: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Relevance of spatial information• Spatial information

• describes the natural and built environment in which citizens live their lives and consume goods and services

• represents a key dimension when considering equity of access to services and when measuring efficiency and effectiveness of service delivery .

• provides a meaningful point of common reference when "overlaying" and analysing data from multiple sources • official statistics, data about infrastructure and services, data from administrative datasets, data

from social media

Page 5: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Explosion over the past decade in availability & use of spatial information• If the first big bang created space and time, a second big bang has resulted in

prevalence of spatial information?

• Availability• GPS (Global Positioning System)• Cellular networks• RFID (Radio-frequency identification)• Automated geocoding for street and IP addresses

• Use• Google Maps

• Including Navigation and Transit

• Google Earth• (Relatively) user friendly & community supported open source geospatial tools

• Including GeoTools and GeoServer

Page 6: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Spatial Data Infrastructure (SDI)• A data infrastructure implementing a framework of geographic

data, metadata, users and tools that are interactively connected in order to use spatial data in an efficient and flexible way

• Examples• INSPIRE• 16 national examples listed on GGIM website

Page 7: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Standardisation driven by industry needs• Use of GIS (Geographic Information Systems) became prevalent

within the industry during the 1980s.

• Led to a need to be able to exchange data and metadata between different GIS.• Defacto industry standards emerged in the early 1990s (eg shapefiles)

• Rise of the Open Geospatial Consortium (OGC) from 1994• Currently comprises 475 companies, government agencies and universities• Consensus process to develop publicly available interface standards• Aim is to enable geoprocessing technologies to interoperate, or plug & play• OGC has standardised 50+ specifications,

• Includes GML, KML (used widely by Google), WMS (Web Map Service), WFS (Web Feature Service)

• Also includes registry services, catalogue services, access control, semantic web

Page 8: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Focus on metadata• Standardisation of geographic metadata at the national level

during the 1990s.• International harmonisation begins in 1999• ISO 19115 ("Geographic Information - Metadata“) released 2003• ISO 19139 released 2007 to provide standard XML representation

for metadata that corresponded semantically with ISO 19115• Some analogies with work to represent GSIM using SDMX and DDI

• Many national and transnational implementations use or profile the ISO metadata standard(s), eg• INSPIRE• FGDC

• Covers identification of resources (can be used for cataloguing traditional library resources), spatial extent (eg bounding box), temporal extent, data quality etc

• ISO 19115 ("Geographic Information - Metadata“) released 2003• ISO 19139 released 2007 to provide standard XML representation

for metadata that corresponded semantically with ISO 19115

• Use of GIS (Geographic Information Systems) became prevalent within the industry during the 1980s.

• Led to a need to be able to exchange data and metadata between different GIS.• Defacto industry standards emerged in the early 1990s (eg shapefiles)

• Rise of the Open Geospatial Consortium (OGC) from 1994• Currently comprises 475 companies, government agencies and universities• Consensus process to develop publicly available interface standards• Aim is to enable geoprocessing technologies to interoperate, or plug & play• OGC has standardised 50+ specifications,

• Includes GML, KML (used widely by Google), WMS (Web Map Service), WFS (Web Feature Service)

• Also includes registry services, catalogue services, access control, semantic web

Page 9: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Global Geospatial Information Management (GGIM) initiative• Arose from UNSC 2010 paper from Brazilian NSI requesting focus

on GGIM• UNSC recognized the importance of the integration of geographic and

statistical information

• GGIM operates under auspices of the UNSD & UN Cartographic Section

• In their second meeting, in August 2012, GGIM Committee of Experts concluded

• One of nine areas for focus in the future was linking geospatial information to statistics.

• A Programme Review by the UNSC would be helpful to support the development of a Statistical Geospatial Framework in National Statistical Systems.• ABS volunteered to assist and to prepare a paper for consideration by the UNSC in 2013.

Page 10: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

UNSC Programme Review• Objectives

• To present a review of current geospatial capabilities and capacity within NSOs• To propose roles for NSOs in geospatial activities, with a particular focus on

integrating statistical and geospatial information• To propose how geospatial activities could be further developed by NSOs

within countries, and understand user needs driving particular geospatial data developments

• To explore how NSOs do, or should be doing, geocoding of their data; and• To explore how to set standards that integrate data between the two

communities.

• Survey of Linking Geospatial Information to Statistics, circulated in October 2012• 50 questions• 53 NSOs responded• Results reported to UNSC, including detailed analysis.

Page 11: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Developing an international statistical geospatial framework (1)• Main paper from ABS to UNSC 2013 addressed

• The need for linking socioeconomic information to a location• The current situation (summarising the findings of the survey)• The future information agenda (such as requirements beyond the Millennium

Development Goals and to inform Sustainable Development)• Proposed future directions

Page 12: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Developing an international statistical geospatial framework (2)• Recommendations (fundamentals were endorsed by UNSC)

• An international conference be convened to identify and address common issues relating to linking socioeconomic information to a location, including developing best practice principles

• Linkages between relevant statistical and geospatial organizations be formalized, building on the efforts of the UN Committee of Experts on GGIM and working with other relevant international entities, including HLG.

• The approach used in Australia through the Statistical Spatial Framework (SSF) be examined as a possible methodology to guide a common global approach to linking socioeconomic information to a location.

• A group of experts be established at an international level to further the development of a common approach to linking socioeconomic information to a location.

• In developing national statistics plans, countries be encouraged to consider the possibilities for linking statistical and spatial information, consistent with their development priorities

• As national statistics offices undertake information management infrastructure transformation activities, consideration be given to adding geospatial capability, including the geocoding of addresses

Page 13: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Bringing it back home• HLG Projects for 2013

• Frameworks and Standards for Statistical Modernization Project• Common Statistical Production Architecture Project ("Plug and Play")

• Under “Frameworks and Standards” Work Package 6 is• provide an initial assessment of the role of geo-spatial standards in the

modernisation of official statistics, including how they may relate to the GSBPM and the GSIM.

• Examples of possible areas for review• How should relevant attribute components within unit and dimensional data structures

used in statistics be denoted as geospatial in nature (eg if they contain geographical co-ordinates or codes for geographic areas) and linked to relevant geospatial metadata (eg spatial representation information, reference system information)?

• Both statistical and geospatial metadata include data quality information. Quality in the latter case typically refers to precision of spatial positioning. How can we manage the two types of quality information, making the right information available to the right user?

• Both statistical and geospatial metadata support the identification, description and subsequent discovery of resources. How can they best work together?

• Both statistical and geospatial metadata standards refer to the temporal extent of data.

Page 14: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Australian Statistical Spatial Framework (SSF)Context

Page 15: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Key points• The concept of location or ‘place’ is now a key driver for the ABS

and other organisations collecting, compiling, analysing and disseminating socio-economic statistical information

• SSF is aimed at providing a consistent and common spatial approach for all providers of socio-economic information.• Using a common approach will greatly simplify the process of linking socio-

economic data sets to help better understand a wide range of complex issues, improving the ability of government and the community to make more informed decisions.

• SSF is essentially a bridge - a bridge between the statistical and spatial communities and the systems in which they operate.• The common element in this bridge is geography. Geography draws the

socio-economic into the spatial community's environment, and makes it available for use within that environment.

• SSF needs to meet ABS, Australian Government and National needs and support International interoperability.

Page 16: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure
Page 17: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Expected outcomes• By standardising the process of integrating a range of socio-

economic information within a location context, the SSF is expected to enable• Improved planning for regional economies and communities• Targeted service delivery at the small area level; and• Community level decision making

• In addition, the Framework will support the considerable efforts currently being made to bring a range of data together to better understand the causes, impacts and responses at the local level to national and global concerns such as climate change and sustainable development

Page 18: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Conclusions• Spatial data is increasingly prevalent and increasingly used by

governments and the community.• UNSC and others recognise the importance and value of the

integration of geospatial information and statistics in supporting social, economic and environmental policy decision-making

• Developing, agreeing and applying statistical spatial frameworks can facilitate this integration at the national & international levels

• UNSC, UNSD and HLG are committed to taking practical steps to establish such frameworks

• The expertise and experience of specialists in statistical information management, including statistical metadata, will make a vital contribution to defining frameworks which serve as the "bridge" between the spatial and statistical communities

Page 19: Statistical and Spatial  Frameworks,  Standards and Data  Infrastructure

Possible considerations for METIS participants• What additional information and/or actions might help them

better to contribute to this work at the national and/or international level?

• How might contributions from the statistical metadata community best be progressed?

• What collaboration arrangements would be best across the statistical metadata community and beyond that community (eg with geospatial data and metadata experts)?