IUSS WGS SIS - Distributed services, information systems, digital products, the European GS Soil Project, communicating infrastructures - Rainer Baritz, Hannes I. Reuter, Peter Wilson, Einar Eberhardt on behalf of the IUSS WG SIS and the GS Soil Project
3. Technical introduction to the Digital Soil MappingFAO
Digital soil mapping involves creating digital maps of soil types and properties by using numerical models. It utilizes legacy soil data such as soil samples, profiles, and maps along with spatial data on soil forming factors like climate, organisms, relief, parent material, and lithology. Common soil inference models used in digital soil mapping include data mining techniques like regression, classification trees, and neural networks as well as geostatistical methods. The process produces quantified estimates of prediction uncertainty since soil variation cannot be perfectly modeled.
The document discusses methods for generating a global soil organic carbon map. It describes using data from the Harmonized World Soil Database to calculate soil organic carbon stocks in the topsoil layer (0-30 cm) and subsoil layers (30-100 cm), and combining these values to estimate stocks to a 1m depth. Where data is missing, values are supplemented from other sources. The document also discusses analytical methods for determining soil organic matter and carbon, and calculating carbon stocks based on parameters like bulk density and stone content. Upscaling procedures are described, with digital soil mapping identified as the preferred method.
Global Soil Data Task, part of Earth Data Sets - Vincent van EngelenFAO
The document discusses the Global Soil Data Task, which is part of the Group on Earth Observations' effort to build a Global Earth Observation System of Systems (GEOSS) to provide decision-makers access to environmental data. The task aims to make harmonized soil data available through web services at global, regional, and national levels. Main activities include providing soil area-class and property data surfaces from initiatives like the Harmonized World Soil Database and GlobalSoilMap.net. Key players include ISRIC, JRC, USDA-NRCS, FAO, and ISSCAS.
3. Technical introduction to the Digital Soil MappingFAO
Digital soil mapping involves creating digital maps of soil types and properties by using numerical models. It utilizes legacy soil data such as soil samples, profiles, and maps along with spatial data on soil forming factors like climate, organisms, relief, parent material, and lithology. Common soil inference models used in digital soil mapping include data mining techniques like regression, classification trees, and neural networks as well as geostatistical methods. The process produces quantified estimates of prediction uncertainty since soil variation cannot be perfectly modeled.
The document discusses methods for generating a global soil organic carbon map. It describes using data from the Harmonized World Soil Database to calculate soil organic carbon stocks in the topsoil layer (0-30 cm) and subsoil layers (30-100 cm), and combining these values to estimate stocks to a 1m depth. Where data is missing, values are supplemented from other sources. The document also discusses analytical methods for determining soil organic matter and carbon, and calculating carbon stocks based on parameters like bulk density and stone content. Upscaling procedures are described, with digital soil mapping identified as the preferred method.
Global Soil Data Task, part of Earth Data Sets - Vincent van EngelenFAO
The document discusses the Global Soil Data Task, which is part of the Group on Earth Observations' effort to build a Global Earth Observation System of Systems (GEOSS) to provide decision-makers access to environmental data. The task aims to make harmonized soil data available through web services at global, regional, and national levels. Main activities include providing soil area-class and property data surfaces from initiatives like the Harmonized World Soil Database and GlobalSoilMap.net. Key players include ISRIC, JRC, USDA-NRCS, FAO, and ISSCAS.
This document provides background information on a training regarding the development of national soil organic carbon stock maps. It discusses the establishment of the Asian Soil Partnership in 2012 and its 5 pillars of action, with an emphasis on Pillar 4 involving soil data and information. Developing national soil organic carbon maps is important for reporting on sustainable development goals and understanding climate change. The training will focus on building countries' capacity to map soil organic carbon according to Global Soil Partnership specifications to contribute to the Global Soil Organic Carbon Map and the Global Soil Information System.
The document discusses cooperation between various global organizations working on soil issues. It describes a capacity development program to introduce digital soil mapping concepts and techniques to soil scientists. It also mentions that the Global Soil Partnership is tasked with providing support on soil carbon issues and was approached by the UNCCD to share information and contribute to improving soil carbon knowledge. It discusses collaboration between the GSP and other intergovernmental bodies on conducting a global soil organic carbon assessment.
Opening SOC training course FAO - June 2017ExternalEvents
The presentation was given by Mr. Rik van den Bosh, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
Este documento presenta el marco de políticas regionales de la FAO para América Latina. Resume el contexto general del sector pecuario en la región, que produce el 25% de la carne vacuna mundial. También describe el marco global de los Objetivos de Desarrollo Sostenible y el marco regional del Plan SAN CELAC con sus cuatro pilares y once líneas de acción. Finalmente, identifica los desafíos de mejorar las políticas para la producción pecuaria familiar, sanidad animal y desarrollo sostenible del sector, así como oportun
Genome sequencing for animal health - input and impactFAO
This document discusses how genome sequencing can be used for animal health monitoring and disease control. It provides examples of how sequencing has been used to monitor virus distribution and evolution, evaluate vaccine matching, and improve molecular epidemiology and diagnostic assays. The document also gives examples of impacts in Indonesia and Egypt, such as informing avian influenza control policies and improving knowledge of circulating H5N1 viruses. It concludes that sequence data is a key component of disease control and that sharing sequences is important, and FAO is working to build sequencing capacity and promote data sharing.
Protecting plant biodiversity: The ITPGRFA, genome sequencing and the relevan...FAO
The presentation includes information on the ITPGRFA's objectives, the Nagoya Protcol and its comparison with the treaty. Further information on connecting Genomics and other type of information with the Global Information System are also available in the presentation.
http://tiny.cc/FAO-COAG-GS
http;//www.fao.org
The Nagoya Protocol is a supplementary agreement to the Convention on Biological Diversity that provides a legal framework for fair and equitable sharing of benefits from genetic resources. It was adopted in 2010 in Nagoya, Japan and entered into force in 2014. The protocol aims to establish predictable conditions for access to genetic resources and ensure benefit-sharing when resources leave the contracting party. It applies to genetic resources and traditional knowledge covered by the CBD, and sets obligations for access, benefit-sharing, and compliance measures to support its implementation at the domestic level.
Genomic sequencing a sub-disciplinary branch of genetics and difference between the two sequencers used to sequence the genome basically automated sequencer and fluorescence sequencers and its applications.
This document discusses the history and various methods of DNA sequencing. It begins with a brief overview of DNA sequencing and its uses. It then outlines some of the major developments in DNA sequencing techniques, including the earliest RNA sequencing in 1972, Sanger sequencing in 1977, and the first complete genome of Haemophilus influenzae in 1995. The document proceeds to provide more detailed explanations of several DNA sequencing methods, such as Sanger sequencing, pyrosequencing, shotgun sequencing, Illumina sequencing, and SOLiD sequencing.
The document discusses genome sequencing and related topics. It begins by defining what a genome is - the complete set of DNA in an organism. It then discusses the different types of genomes, such as prokaryotic and eukaryotic, including nuclear, mitochondrial, and chloroplast genomes. The document also defines genomics as the comprehensive study of whole genomes and all gene interactions, distinguishing it from traditional genetics which focuses on single genes. It outlines some key milestones in genomic sequencing and the technical foundations that enabled sequencing whole genomes. Finally, it describes the main approaches used for genome sequencing projects, including hierarchical shotgun sequencing and whole genome shotgun sequencing.
This document summarizes information from a student's assignment on plant genome sequencing techniques. It discusses early phenotypic selection methods and their limitations. It then summarizes different sequencing strategies used for important crop plants like rice, poplar, and Arabidopsis. These include BAC-by-BAC, whole genome shotgun, and various next-generation sequencing platforms. The document also summarizes applications of sequencing including identifying genes related to rice yield and flowering time and using sequencing to improve potato and maize varieties.
Dynamic memory allocation involves allocating memory at runtime using functions like malloc(), calloc(), and realloc(). Malloc() allocates a block of memory of a specified size and returns a pointer to it. Calloc() allocates memory for an array and initializes it to zero. Realloc() changes the size of a previously allocated memory block. The examples demonstrate allocating 2D arrays dynamically and performing operations like transpose and multiplication on them before freeing the allocated memory.
Sequencing a genome involves determining the order of nucleotides in genetic material like DNA. It is a complex process because genomes are very large, consisting of millions or billions of base pairs, while current technology can only read short stretches of hundreds of base pairs. There were competing methods used by public and private teams to assemble sequenced DNA fragments into full genomes. Some key challenges included incomplete coverage leaving gaps, sequencing errors, and repetitive sequences that are difficult to assemble. Automation and new computational techniques were needed to solve the complex assembly problem at the large scale of the human genome.
This document provides background information on a training regarding the development of national soil organic carbon stock maps. It discusses the establishment of the Asian Soil Partnership in 2012 and its 5 pillars of action, with an emphasis on Pillar 4 involving soil data and information. Developing national soil organic carbon maps is important for reporting on sustainable development goals and understanding climate change. The training will focus on building countries' capacity to map soil organic carbon according to Global Soil Partnership specifications to contribute to the Global Soil Organic Carbon Map and the Global Soil Information System.
The document discusses cooperation between various global organizations working on soil issues. It describes a capacity development program to introduce digital soil mapping concepts and techniques to soil scientists. It also mentions that the Global Soil Partnership is tasked with providing support on soil carbon issues and was approached by the UNCCD to share information and contribute to improving soil carbon knowledge. It discusses collaboration between the GSP and other intergovernmental bodies on conducting a global soil organic carbon assessment.
Opening SOC training course FAO - June 2017ExternalEvents
The presentation was given by Mr. Rik van den Bosh, ISRIC, during the GSOC Mapping Global Training hosted by ISRIC - World Soil Information, 6 - 23 June 2017, Wageningen (The Netherlands).
Este documento presenta el marco de políticas regionales de la FAO para América Latina. Resume el contexto general del sector pecuario en la región, que produce el 25% de la carne vacuna mundial. También describe el marco global de los Objetivos de Desarrollo Sostenible y el marco regional del Plan SAN CELAC con sus cuatro pilares y once líneas de acción. Finalmente, identifica los desafíos de mejorar las políticas para la producción pecuaria familiar, sanidad animal y desarrollo sostenible del sector, así como oportun
Genome sequencing for animal health - input and impactFAO
This document discusses how genome sequencing can be used for animal health monitoring and disease control. It provides examples of how sequencing has been used to monitor virus distribution and evolution, evaluate vaccine matching, and improve molecular epidemiology and diagnostic assays. The document also gives examples of impacts in Indonesia and Egypt, such as informing avian influenza control policies and improving knowledge of circulating H5N1 viruses. It concludes that sequence data is a key component of disease control and that sharing sequences is important, and FAO is working to build sequencing capacity and promote data sharing.
Protecting plant biodiversity: The ITPGRFA, genome sequencing and the relevan...FAO
The presentation includes information on the ITPGRFA's objectives, the Nagoya Protcol and its comparison with the treaty. Further information on connecting Genomics and other type of information with the Global Information System are also available in the presentation.
http://tiny.cc/FAO-COAG-GS
http;//www.fao.org
The Nagoya Protocol is a supplementary agreement to the Convention on Biological Diversity that provides a legal framework for fair and equitable sharing of benefits from genetic resources. It was adopted in 2010 in Nagoya, Japan and entered into force in 2014. The protocol aims to establish predictable conditions for access to genetic resources and ensure benefit-sharing when resources leave the contracting party. It applies to genetic resources and traditional knowledge covered by the CBD, and sets obligations for access, benefit-sharing, and compliance measures to support its implementation at the domestic level.
Genomic sequencing a sub-disciplinary branch of genetics and difference between the two sequencers used to sequence the genome basically automated sequencer and fluorescence sequencers and its applications.
This document discusses the history and various methods of DNA sequencing. It begins with a brief overview of DNA sequencing and its uses. It then outlines some of the major developments in DNA sequencing techniques, including the earliest RNA sequencing in 1972, Sanger sequencing in 1977, and the first complete genome of Haemophilus influenzae in 1995. The document proceeds to provide more detailed explanations of several DNA sequencing methods, such as Sanger sequencing, pyrosequencing, shotgun sequencing, Illumina sequencing, and SOLiD sequencing.
The document discusses genome sequencing and related topics. It begins by defining what a genome is - the complete set of DNA in an organism. It then discusses the different types of genomes, such as prokaryotic and eukaryotic, including nuclear, mitochondrial, and chloroplast genomes. The document also defines genomics as the comprehensive study of whole genomes and all gene interactions, distinguishing it from traditional genetics which focuses on single genes. It outlines some key milestones in genomic sequencing and the technical foundations that enabled sequencing whole genomes. Finally, it describes the main approaches used for genome sequencing projects, including hierarchical shotgun sequencing and whole genome shotgun sequencing.
This document summarizes information from a student's assignment on plant genome sequencing techniques. It discusses early phenotypic selection methods and their limitations. It then summarizes different sequencing strategies used for important crop plants like rice, poplar, and Arabidopsis. These include BAC-by-BAC, whole genome shotgun, and various next-generation sequencing platforms. The document also summarizes applications of sequencing including identifying genes related to rice yield and flowering time and using sequencing to improve potato and maize varieties.
Dynamic memory allocation involves allocating memory at runtime using functions like malloc(), calloc(), and realloc(). Malloc() allocates a block of memory of a specified size and returns a pointer to it. Calloc() allocates memory for an array and initializes it to zero. Realloc() changes the size of a previously allocated memory block. The examples demonstrate allocating 2D arrays dynamically and performing operations like transpose and multiplication on them before freeing the allocated memory.
Sequencing a genome involves determining the order of nucleotides in genetic material like DNA. It is a complex process because genomes are very large, consisting of millions or billions of base pairs, while current technology can only read short stretches of hundreds of base pairs. There were competing methods used by public and private teams to assemble sequenced DNA fragments into full genomes. Some key challenges included incomplete coverage leaving gaps, sequencing errors, and repetitive sequences that are difficult to assemble. Automation and new computational techniques were needed to solve the complex assembly problem at the large scale of the human genome.
The document discusses genome sequencing in vegetable crops. It provides an overview of the history and different generations of sequencing including Sanger sequencing, second generation sequencing using platforms like Roche 454 and Illumina, and third generation sequencing. It then summarizes key vegetables whose genomes have been sequenced like potato, melon, cabbage, and discusses findings from their sequencing projects including genome size, number of predicted genes, and genes of interest identified.
Similar to IUSS WGS SIS - Distributed services, information systems, digital products, the European GS Soil Project, communicating infrastructures - Rainer Baritz, Hannes I. Reuter, Peter Wilson, Einar Eberhardt on behalf of the IUSS WG SIS and the GS Soil Project
Global Soil Information System (GloSIS) - Yusuf YiginiFAO
The document discusses Pillar 4 of the Global Soil Partnership, which aims to establish a Global Soil Information System (GloSIS) to monitor global soil resources. It outlines that GloSIS will be a federated system relying on national soil information systems and capacities. It also describes some key components and data products of GloSIS, including soil profile databases, soil property grids, and statistics. Participation in GloSIS can be through directly implementing a node, using a reference node implementation, or having data supported on a central node. The system is being developed and implemented through the collaboration of countries and soil experts.
Spatial data infrastructure in KyrgyzstanUnison Group
The document discusses the limitations of Kyrgyzstan's spatial data infrastructure and the implications for climate adaptation efforts. It finds that there is currently no national SDI, and data exists in silos with poor coordination and data sharing between institutions. This poses challenges for climate adaptation projects that require spatial data on topics like boundaries, satellite imagery, and climate/weather. The document recommends establishing a working group to develop an NSDI through improved data access, standards, and awareness of SDI benefits. This could help adaptation efforts and unlock economic opportunities through increased transparency, efficiency and investment.
Department of Geography and Geoinformation Science Seminar, George Mason University, Falls Church, VA, September 2015.
Increasingly, GIS is part of the collaboration between computer scientists, information scientists, and domain scientists to solve complex scientific questions. Successfully addressing scientific problems, such as informing regional decision- and policy-making for coastal zone management and marine spatial planning, requires integrative and innovative approaches to analyzing, modeling, and developing extensive and diverse data sets. The current chaotic distribution of available data sets, lack of documentation about them, and lack of easy-to-use access tools and computer modeling and analysis codes are still major obstacles for scientists and educators alike. Contributing solutions to these problems is part of an emerging science agenda at Esri for a range of environmental, conservation, climate and ocean sciences that will be discussed. The talk will highlight some recent projects in progress, including a new global map of ecological land units, new tools to support multidimensional scientific data, continued work on an ocean basemap, and more.
The document discusses open geo-spatial data and spatial data infrastructures. It provides an overview of key concepts including open data, geographic information systems (GIS), spatial data formats and standards, and spatial data infrastructure initiatives like INSPIRE which aim to make spatial data interoperable across Europe. The document also discusses global open data efforts like the Group on Earth Observations (GEO) and GEOSS, as well as principles for open data and how data can be made more open and accessible.
Overview of the world of geospatial metadata, and the role of the EDINA service GoGeo in creating, saving, and discovering it. Presented on 19 June 2014 by Tony Mathys in Aberdeen, Scotland.
Presented by Tony Mathys at a Current Issues and Applications of the Geospatial Technologies Lecture, Department of Geography and Environment, Aberdeen University, 24 February 2012
The document discusses establishing geospatial analysis capabilities within an exploration environment. It outlines collecting all relevant exploration data, representing it properly in a GIS database, and generating continuous geospatial grids using deterministic and geostatistical methods. These grids would support spatial analysis and decision making by allowing visualization and queries of parameters like probability of success. Maintaining data quality and understanding relationships between different data types is important for effective analysis.
Defining Digital Earth as a virtual representation of all digital information with a geospatial component, this geography attempts to delineate the scope and elements of Digital Earth. The framework for this geography is a set of layers applicable to describing an information system. From bottom to top the layers are physical, data, information, knowledge, decisions and actions. Conclusions of this geography are that some technologies are sufficient for a Digital Earth to come into existence, but some technologies, in particular in the upper layers, need to be developed. Three conclusions are listed in this abstract.
In the physical and data layers, the explosive growth of Internet provides access to much Digital Earth data. However, the bandwidth necessary for high-end Digital Earth clients will not be widely deployed for some time. In the near term it will be necessary to have Digital Earth access points in public places like museums where high bandwidth is available.
Digital Earth information volume is estimated by assuming a fraction of all digital information that has a geospatial component. Estimates place the total volume of recorded information at several thousand petabytes, i.e., several exabytes. It has been regularly postulated in the geographic community that half or more of all information has a geospatial component. Even though we will soon have the capacity to digitally record this volume of information, most of of it will never be looked at by a human. Tools are needed for auto-summarization, distilling the information into knowledge with lower volume and higher semantic content.
To allow decisions and actions based on the knowledge of Digital Earth requires analysis of the knowledge using tools particular to the geospatial domain. As Digital Earth will exist in a distributed service environment based on standards for interoperability, the standards must address the particulars of geospatial semantics. Syntax standards for transporting semantic information (e.g., XML) have been defined and extended with geospatial structures. Standards for achieving shared understandings ("domain semantics") are yet to be developed. Beyond domain semantics, the validity of chaining services on geospatial features ("process semantics") is less developed.
Item i ia e. glo-sis development - yusuf yigini, fenny van egmondSoils FAO-GSP
This document discusses the development of GloSIS (Global Soil Information System). It provides an overview of both short term goals (GloSIS 1.0) and long term goals (GloSIS 2.0). In the short term, the goal is to help countries organize and share their soil data through national nodes and a discovery hub. In the long term, the goal is to develop a fully functional system for harmonized data storage, exchange, and analysis using semantic web technologies and standards. Key aspects discussed include node development, the discovery hub, data exchange standards, and ongoing work to refine the GloSIS domain model to support linked data approaches.
The document discusses using smartphone and tablet technologies to integrate INSPIRE geospatial data infrastructure. It describes projects like HABITATS that modeled environmental data themes in compliance with INSPIRE. Different use cases for regional and global data are examined. Basic and advanced techniques for transforming data between regional models and INSPIRE are outlined. The document also introduces the HABITATS Reference Laboratory concept for supporting cross-scenario applications and testing local data sharing. It identifies opportunities to make INSPIRE data more accessible through mobile and social applications.
GI2013 ppt kafka&team-inspire in pocketIGN Vorstand
The document discusses integrating INSPIRE geospatial data standards with mobile devices. It describes the HABITATS project which designed environmental data and metadata models compliant with INSPIRE for themes like habitats and species distribution. The benefits of participating in INSPIRE technical working groups are outlined. Various use cases for regional and global data at different scales are examined, along with challenges of cross-border data harmonization. Basic and advanced techniques for transforming data between models are presented, including using SQL, ontologies and taxonomies. The HABITATS Reference Laboratory is introduced as a hub supporting INSPIRE data sharing and testing across pilot applications. Ideas are raised about making INSPIRE data more accessible through mobile and social applications
This document provides an overview of seven platforms for managing and analyzing large Earth observation data: Google Earth Engine, Sentinel Hub, Open Data Cube, SEPAL, OpenEO, JEODPP, and pipsCloud. It describes each platform's architecture, data storage, processing capabilities, data access methods, and data abstractions. It also compares the platforms based on their support for capabilities of interest to the Earth observation community, such as reproducible science.
This tool solves a real problem in the environmental inventory industry and makes a valuable open data set more accessible.
The NJDEP maintains a statewide wildlife habitat data set that details conservation requirements related to environmental regulations. This is an open data set, but accessibility is limited since working with the one million habitat areas often requires knowledge of GIS software. Using desktop GIS software, a site-specific search is a time-intensive process, taking minutes or hours to run geoprocessing operations for specific properties.
Now, a user can draw a custom area in a browser window and return results in seconds.
Learn about how the project was built in this presentation.
As part of the GSP’s capacity development and improvement programme, FAO/GSP have organised a one week training in Izmir, Turkey. The main goal of the training was to increase the capacity of Turkey on digital soil mapping, new approaches on data collection, data processing and modelling of soil organic carbon. This 5 day training is titled ‘’Training on Digital Soil Organic Carbon Mapping’’ was held in IARTC - International Agricultural Research and Education Center in Menemen, Izmir on 20-25 August, 2017.
Pillar 4 Implementation and P4WG Progress Report - Yusuf YiginiFAO
Fourth Working Session of the International Network of Soil Information Institutions (INSII)
6-8 November 2018 | FAO HQ – German Room, Rome, Italy
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Agenda of the 5th NENA Soil Partnership meetingFAO
The Fifth meeting of the Near East and North African (NENA) Soil Partnership will take place from 1-2 April 2019 in Cairo, Egypt. The objectives of the meeting are to consolidate the NENA Soil Partnership, review the work plan, organize activities to establish National Soil Information Systems, agree to launch a Regional Soil Laboratory for NENA, and strengthen networking. The meeting agenda includes discussions on soil information systems, a soil laboratory network, and implementing the Voluntary Guidelines for Sustainable Soil Management. The performance of the NENA Soil Partnership will also be assessed and future strategies developed.
This document summarizes the proceedings of the first meeting of the Global Soil Laboratory Network (GLOSOLAN). GLOSOLAN was established to harmonize soil analysis methods and strengthen the performance of laboratories through standardized protocols. The meeting discussed the role of National Reference Laboratories in promoting harmonization, and how GLOSOLAN is structured with regional networks feeding into the global network. Progress made in 2018 included registering over 200 laboratories, assessing capacities and needs, and establishing regional networks. The work plan for 2019 includes further developing regional networks, standard methods, a best practice manual, and the first global proficiency testing. The document concludes by outlining next steps to launch the regional network for North Africa and the Near East.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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IUSS WGS SIS - Distributed services, information systems, digital products, the European GS Soil Project, communicating infrastructures - Rainer Baritz, Hannes I. Reuter, Peter Wilson, Einar Eberhardt on behalf of the IUSS WG SIS and the GS Soil Project
1. IUSS WGS SIS
Distributed services, information
systems, digital products, the European
GS Soil Project, communicating
infrastructures
Rainer Baritz, Hannes I. Reuter, Peter Wilson, Einar Eberhardt
on behalf of the IUSS WG SIS and the GS Soil Project
2. Networking among data providers
International Soil Science
Society (IUSS)
WG Soil Information
Standards (SIS)
under the Commissions of
Pedometrics and Soil Geography,
Chair: Peter Wilson (CSIRO)
Technical support to data
holders, maximise data
availablility, utilize modern IT
Increase network world
wide
EU ICT project GS Soil
with 18 EU member states,
mostly European Soil Bureau
Network (ESBN)
Test ISO SoilML, test INSPIRE,
apply Web-GIS, harmonize
legacy data, build portal
Implementation all over Europe
Framework for integrating legacy
data towards new products
2 examples will be now provided
3. Mission
To develop, promote and maintain internationally recognized and
adopted standards for the exchange and collation of consistent
harmonized soils data and information worldwide
Goals
provide leadership and focus for collaboration and coordination
of soil information standards efforts
increase accessibility and use of soil data and information for
cross-sectoral issues
4. inaugural meeting Berlin 16-17 June 2011
• Representation from key international soil information
initiatives including GlobalSoilMap.net, ISO, INSPIRE,
OGC
• Agreed Terms of Reference
• Chair - Peter Wilson, Vice Chair - Rainer Baritz
• Identified 4 key areas for activity
• Developed work plan with specific short term and longer
term activities
IUSS WG SIS
5. IUSS WG SIS
4 Pillars
1.
Network
building
- web site (ISRIC)
- Support GSP
- Support GEOSS-
Global Soil Data
4.
Web processing
- ISO SoilML, other
standards (product-
/country-specific)
- Data exchange of raster
data
- Best practice guidance
2.
Soil data
exchange
format
- Generate access to data
(metadata, view-/download
services)
- Address harmonization issues
3.
Data availability
8. Provider A
Product A: WMS, metadata
Product B: WMS, metadata
Provider B
Product A: WFS, WMS, metadata
Product B: WMS, metadata
Provider C
Product A: metadata
Product B: onlineshop
Product B: WPS
Distributed System (data communication/exchange)
Portal World Soil Data Centre
Other Portals
to harvest
Harvesting, guidance, metadata editing, domain-
specific services (best practices, technical +
semantic support , Viewer, WPS, methodologies,
imlplementatinwhere resources are limited
Viewer, WPS
Other
international
Data Centres
Climate data,
other data
Nodes
„Relais“
stations
9. Next steps regarding networking
- Improve web site
- Active communication with networks: invite further
information system holders to become members
(ESBN, GlobalSoilMap, etc.)
- Boost activity: GSP governance could help
WG SIS Roadmap
10. IUSS WG SIS
4 Pillars
1.
Network building
- web site (ISRIC)
- Support GSP
- Support GEOSS- Global
Soil Data
4.
Web
processing
- ISO SoilML, other
standards (product-
/country-specific)
- Data exchange of
raster data
- Best practice
guidance
2.
Soil data
exchange
format
- Generate access to data
(metadata, view-/download
services)
- Address harmonization issues
3.
Data availability
11. 2. Pillar: soil data exchange format
- differently constructed local data bases, managed with different
software, and different export formats
- Additional information (not transported) is needed to understand
the relationships between content features (to combine the tables,
site description with horizon parameters
SIS
DBMS*)
geometric-topological data management semantic data management
- profile- and analytical data bases
- classification/nomenclature
- parameter keys
- map data base (images, polygons)
soil and auxiliary mapping data
- topologies
map unit
attributes
GIS routines queries/statistics
ODBC
GIS
method data base
metadata base
add-ins
Where the data stored, and how are they currently exchanged?
12. Analysis of data bases to find generic
exchange principles to be introduced to
data exchange recommendations
Bodemkaartvlakken
KAARTVLAK_ID
Shape
TYPE_CLASSIFICATIE
BODEMTYPE
EENDUIDIGE_LEGENDE
KAARTNR
KAARTBOEKJE
STREEK
Textuur
TEXTUUR
OMSCHR
TEXTUUR1
TEXTUUR2
TEXTUUR3
Geomorfologisch
KAARTVLAK_ID
TYPE_CLASSIFICATIE
OMSCHR_BODEMTYPE
SERIE
SUBSERIE
TYPE
SUBTYPE
SUBSTRAAT
Variprof
VARIPROF
OMSCHR
VARIPR1
VARIPR2
Varimoma
VARIMOMA
OMSCHR
VARIMO1
VARIMO2
VARIMO3
Substraat
SUBSTRAAT
OMSCHR
SUBG1
SUBG2
SUBGM1
SUBGSM2
SUBM1
Profiel
PROFIEL
OMSCHR
Drainage
DRAINAGE
OMSCHR
Morfogenetisch
KAARTVLAK_ID
TYPE_CLASSIFICATIE
MORFOGENETISCH
BODEMSERIE
OMSCHR_BODEMSERIE
TEXTUUR
DRAINAGE
PROFIEL
SUBSTRAAT
VARIMOMA
VARIPROF
FASE
STREEK
STREEK
OMSCHR_STREEK
BCODE
1
n
1
1
1
1
n
n
n
n
n
n
1
1
1
1
1
1
Bodemkaartvlakken
KAARTVLAK_ID
Shape
TYPE_CLASSIFICATIE
BODEMTYPE
EENDUIDIGE_LEGENDE
KAARTNR
KAARTBOEKJE
STREEK
Textuur
TEXTUUR
OMSCHR
TEXTUUR1
TEXTUUR2
TEXTUUR3
Geomorfologisch
KAARTVLAK_ID
TYPE_CLASSIFICATIE
OMSCHR_BODEMTYPE
SERIE
SUBSERIE
TYPE
SUBTYPE
SUBSTRAAT
Variprof
VARIPROF
OMSCHR
VARIPR1
VARIPR2
Varimoma
VARIMOMA
OMSCHR
VARIMO1
VARIMO2
VARIMO3
Substraat
SUBSTRAAT
OMSCHR
SUBG1
SUBG2
SUBGM1
SUBGSM2
SUBM1
Profiel
PROFIEL
OMSCHR
Drainage
DRAINAGE
OMSCHR
Morfogenetisch
KAARTVLAK_ID
TYPE_CLASSIFICATIE
MORFOGENETISCH
BODEMSERIE
OMSCHR_BODEMSERIE
TEXTUUR
DRAINAGE
PROFIEL
SUBSTRAAT
VARIMOMA
VARIPROF
FASE
STREEK
STREEK
OMSCHR_STREEK
BCODE
1
n
1
1
1
1
n
n
n
n
n
n
1
1
1
1
1
1
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Soil name - national
classification
Soil name – FAO98
Soil name–WRB2006
Soil texture class
(according to Katchinsky)
SMU
Soil name - national
classification
Soil name – FAO98
Soil name–WRB2006
Soil texture class
(according to Katchinsky)
SMU
Soil profile name (abbreviation
of sub-region name +soil
profile number)
Geographic coordinates
Land use
Parent material
Depth of A horizon and the
whole profile; Rcode (depth to
obstacles for root);
Soil Profile
Soil profile name (abbreviation
of sub-region name +soil
profile number)
Geographic coordinates
Land use
Parent material
Depth of A horizon and the
whole profile; Rcode (depth to
obstacles for root);
Soil Profile
Horizon number
Designation
Upper and bottom
boundaries of soil
horizons
Soil horizon
Horizon number
Designation
Upper and bottom
boundaries of soil
horizons
Soil horizon
Horizon number
Designation
Color; Density;
Structure
morphological
description
Horizon number
Designation
Color; Density;
Structure
morphological
description
Horizon number
Designation
Upper and bottom boundaries of
sampling depth
Soil particles size distribution
(according to Katchinsky );
hygroscopic water content
physical properties
(measured)
Horizon number
Designation
Upper and bottom boundaries of
sampling depth
Soil particles size distribution
(according to Katchinsky );
hygroscopic water content
physical properties
(measured)
Horizon number
Designation
Upper and bottom boundaries of
sampling depth
Humus; pH (in KCl); pH (in H2O);
carbonates; total N, P electrical
conductivity (for saline soils);
chemical properties
(measured)
Horizon number
Designation
Upper and bottom boundaries of
sampling depth
Humus; pH (in KCl); pH (in H2O);
carbonates; total N, P electrical
conductivity (for saline soils);
chemical properties
(measured)
SMU
Soil associations
Landscape
polygons
SMU
Soil associations
Landscape
polygons
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The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again.
The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x
The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If th
13. Data exchange - principles
- Allows the harvesting, reproduction and processing of data
from various sources building on data exchange standards
- Integration of data between different themes and topics is
easier (see also data infrastructures, e.g. GEOSS architecture,
SEIS, national systems, etc.)
- Data exchange: structured XML files
- Data will not anymore provided to an individual user, each time,
again, but only once based on standardized data exchange
- For the handling of domain-specific XML/GML, there will be
increasingly available and user-friendly capacities (GIS
software) which utilize complex features like soil profiles
combined with polygons
Where do we go with data exchange – Web-GIS
XML: eXtensible
Mark up Language
Standard for generating documents readable to machines/humans
using a document tree defined by the World Wide Web Consortium
(W3C). XML defines the rules for the structure of such documents
14. ISO 28258 SoilML now draft standard)
Soil Quality - recording and exchange of soil-related data
Definitions of terms and codes used by soil quality experts
Term Dictionary
Concept of soil data
Map units, sites, soil profiles, soil horizons/depth classes, samples, analysis
Empty structure files (XSD) provided
User (data holder) receives 2 structure files (XSD: data content and
parameter descriptions such as codes)
Guidance (handbook) and schema mapping (transport
- GS Soil project together with WG SIS will develop this handbook
- Tool for extracting data from formatted GIS or data bases into XML/GML
(HALE, Fraunhofer, GS Soil partner)
Resolution 152 Implementation of ISO 28258 as EN-ISO
Soil quality information model
- Compatiple with ISO 19156 Observations and measurements
- UML: soil quality packages (submodels with definition tables and normative
attributes): project, spatial relation, soil mapping, soil observation, soil
sampling, profile description)
Currently, grid/raster features (GSSML) are not included
ElementsofSoilML
15. ISO 28258 SoilML
Usability
Allows all sorts of data, coded and classified, and measured in
different ways, to be exchanged
…in the near future: as Web Feature Services
ISO is draft standard, but different local systems
projects (SOTER), disciplines (GeoSciML and BoreholeML
in OneGeology), countries (Germany: KA5ML, Australia:
OzSoilML; The Netherlands: SIKB-protocol 0101, etc.)
Data transported applying these standards should „communicate“
(receive, understand, process in a single system, e.g. a global portal)
Web
Feature
Services
16. Next steps regarding standards
- Check differences between existing standards: check
validity of SoilML as common denominator, provide
recommendations
- Develop test bed for demonstrating the operational
data exchange (build on the European GS Soil
exercise Cookbook for dat aexchange)
- Develop and offer a simplified data exchange plattform
for core soil profile data
- Incentive to adapt services (e.g. soil profile up-
/download)
WG SIS Roadmap
17. IUSS WG SIS
4 Pillars
1.
Network
building
- web site (ISRIC)
- Support GSP
- Support GEOSS- Global
Soil Data
4.
Web
processing
- ISO SoilML, other
standards (product-
/country-specific)
- Data exchange of
raster data
- Best practice
guidance
2.
Soil data
exchange
format - Generate access to
data (metadata, view-
/download services)
- Address harmoni-
zation issues
3.
Data
availability
18. Elaborate, distributed system, data upload, tools and services
Information: search system
3. Pillar: data availability
- Support to data owners lacking infrastructure:
Metadata upload and cataloguing
Data management: transformation services (e.g.
FAO soil profile description, classification
transformaiton tools), soil profile up-/download
(export XML, linke WISE, etc.)
For data holders lacking a data bases: free
download load of a simple (empty) data base (e.g.
SoDa)
Domain-specific vocabulary development and
service
21. FAO soil profile upload (BGR)
XML-based output
Work stopped because exchange standard
is needed, then new data input mask is
easy (implemented for KA5ML)
Prepare for interactive profile descriptions
and calculations (WPS)
23. GS Soil
“Assessment and strategic development of
INSPIRE compliant Geodata-Services for
European Soil Data”
http://gssoil-portal.eu/
EU-Programme: eContentplus
Duration: 06/2009 – 05/2012 (3 years)
Coordinator: Coordination Center PortalU
(German Environmental Portal)
Consortium: 34 Partner
18 EU member states
24 soil data providers
24. GS Soil Project
Aim:
– Establishment of an European network to improve the
access to INSPIRE related spatial soil data
• improve the accessibility of digital soil data for better
(re)usage and exploitation
• lower the barriers to use data from different sources
• develop methods to produce interoperable spatial soil data,
• develop metadata and content framework for harmonized
soil information
• establish and operate a network of services for spatial
datasets and metadata
Best Practice Network to …
25. Soil in Infrastructures: e.g. INSPIRE
Soil (INSPIRE Annex III)
• Soil Type: classification
• Soil Properties: depth, structure,
particle size distribution, texture, organic
carbon, bulk density, parent material, …
Directly considered topics
Protected Sites (INSPIRE Annex I)
• Soil Protection Areas
Human Health and Safety (INSPIRE Annex III)
• Soil Contamination: dangerous waste, heavy metals, …
Environmental Monitoring Facilities
INSPIRE Annex III)
• Soil Monitoring Facilities & Long Term Observations
Partly covered INSPIRE themes:
Biogeographical
Regions
(INSPIRE Annex III)
SoilRelatedAspectsBasicSoilData
Linked topics
Geology
(INSPIRE Annex II)
Land Cover
(INSPIRE Annex II)
Habitats and Biotopes
(INSPIRE Annex III)
Natural Risk Zones (INSPIRE Annex III)
• Priority Areas for Soil Threats: landslides, soil erosion,
soil compaction, soil organic carbon decline, salinization,
acidification, soil biodiversity loss, …
various
data sources
interoperability
27. Europen Data
Centres
Water (WISE)
EIONET/SEIS
INSPIRE Annex themes „Soil“,
„Environmental Monitoring Facilities“
GS Soil
Portal Soil
eContentplus
Best Practice Networks
OneGeology Europe
Nature-SDIplus
FP6
Orchestra
Humboldt
Cascadoss
European Spatial Data Infrastructure
INSPIRE
GEOSS Data
Architecture
FP7
e-SOTER
(global soil
observing
system)
ENVASSO
RAMSOIL
SDI
Soil
other themes
GMES
Soil Thematic Strategy/
Soil Directive
Environmental
policies
TC 190 (Soil Quality), SC 1 WG 3
(Data codification and management)
ISO
INSPIRE
Drafting Teams
European Soil Bureau
Network (ESBN)
working group „INSPIRE“
ESDAC
JRC
Europen Data
Centres
Water (WISE)
EIONET/SEIS
INSPIRE Annex themes „Soil“,
„Environmental Monitoring Facilities“
GS Soil
Portal Soil
eContentplus
Best Practice Networks
OneGeology Europe
Nature-SDIplus
FP6
Orchestra
Humboldt
Cascadoss
European Spatial Data Infrastructure
INSPIRE
GEOSS Data
Architecture
FP7
e-SOTER
(global soil
observing
system)
ENVASSO
RAMSOIL
SDI
Soil
other themes
GMES
Soil Thematic Strategy/
Soil Directive
Environmental
policies
TC 190 (Soil Quality), SC 1 WG 3
(Data codification and management)
ISO
INSPIRE
Drafting Teams
European Soil Bureau
Network (ESBN)
working group „INSPIRE“
ESDAC
JRC
Changes and benefits – clustering
30. WP 2: IPR assessment
Intellectual property rights assessment
• Evaluation of IPR
103 records have been evaluated:
Data access without restriction: 24 records
Data with restriction: 13 records
Access as raster: 10 records
Access with costs: 1 record
Access with the other restrictions: 2 records
Data with not definitely determined access: 12 records
Data with not defined access: 15 records
Data not available for GS Soil portal: 39 records
WP5: WSS (Web Security Service)
31. WP 2: Content framework standards
Recommendations for legend definitions legend elements
Recommendations for legend stratification
Recommendations for mandatory (SMU/STU-) attribute data (definitions)
Recommendations for soil profile properties (minimum set needed for
important applications - PTF)
Recommendations for parameter definitions (texture class acc. to FAO)
- dependent on product type and scale
⇒ Recommendations include a lot of existing knowledge about
harmonization, but it is now combined into a common framework
for soil data exchange and harmonization in Europe
Figures:
Asch and Troppenhagen (2004)
32. WP 3
Data management and metadata
Soil-specific metadata profile
Soil thesaurus
34. WP 3: introduced soil-specific
metadata elements
Example of the printed map Sheet Freiburg-North
(map representation acc. to the German topographic map 1:200.000)
Encoding
Coordinate reference system
Character Encoding
Source title
Source date
of mapping
Spatial representation
type
Topology level
Thematic Accuracy –
– Classification Correctness
– Misclassification Rate
Source mapping scale
Online digital transfer options
Completeness – Omission
Positional Accuracy – Absolute
or External Accuracy
Furthermore for services:
– Contains operations
– Service version
2. Mandatory/conditional
1. INSPIRE meta data (1205/2008/EC)
3. Optional meta data
35. WP 4
Harmonization and semantic interoperability
set-up of test cases throughout Europe to test
feasibility of harmonization requirements:
- reference terminology (link thesaurus)
- FAO soil profile properties
- WRB
- soil maps
INSPIRE testing, support to ISO 28258 (SoilML)
- cookbook
Link WP5 (IT-implementation) on schema
mapping (transformation service)
⇒ Data Harmonization Best Practice Guidelines
36. Test cases
soil mapping 1:250k
and related scales
soil mapping
at higher
resolutions
thematic
mapping
soil profiles
soil
monitoring
Nomenclature/
classification
(WRB)
− Nordic (FI)
− Balkan (RO, BU, GR)
− UK/IRL/N.-IRL
− Germany (DE)/
France (F)
− Austria (AT)/
Slovakia (SK)
− Belgium
(BE)
− Slovenia
(SL)
− Slovakia
(SK)
− Hungary
(HU)
− Belgium
(BE)
− Germany
(DE)
− Slovakia
(SK)
− Denmark
(DK)
− Austria
(AT)
− Slovakia
(SK)
− Germany
(DE)
− Austria
(AT)
− Hungary
(HU)
− various partners
38. WP 5: GS Soil Portal
- Concept of the Portal- and GS Soil network architecture
- Establishment of semantic services (Thesaurus, Gazeteer)
- Provision of open tools and INSPIRE services for data
providers
- Continuous integration of services and information
- Deployment and operational
manual including guidelines
Discovery (CSW)
View (WMS)
Download (WFS)
GS Soil services
…
40. Similar Terms from
GEMET
…currently further
improved for soil
specific thesaurus
Gazetteer:
…on the basis of
GeoNames,
OpenStretMaps,
GeoHash
WP 5: GS Soil Portal semantic services
42. Conclusions
IUSS WG SIS provides a concept for data exchange
Implemented within the IUSS community (… data
knowledge, methods)
Exchanges and combines the developments in soil
information systems (as an open network) with the
objective to facilitate max. data availability, gobally
Needs to be embedded into a global governance
structure despite the idea of a distributed system
43. Conclusions
GS Soil goes through a large spectrum of soil (data)
networking issues, introduces data providers into data
infrastructures and web-GIS
Provides guidance/best-practice (BP) recommendations
Implementation of BP is not an automatic procedure!
44. OneSoil Map Viewer
(under development)
http://www.isric.org/data/web-map-service
Thank you for your attention!