The document discusses GeoNode, an open source software project that aims to build a next generation Spatial Data Infrastructure (SDI) based on best practices from modern web services. Some key points:
- GeoNode aims to make uploading, sharing, and working with spatial data as easy as blogging by reducing barriers to participation.
- It aligns incentives for contribution and use through features like user profiles, reputation systems, and ability to style and share maps.
- The software implements open standards and APIs to make data accessible and allow other applications to integrate.
A new approach to spatial data infrastructure focused around users and collaboration. Development, Implementation and maintenance of a Geonode portal for local and regional collaboration, geospatial data sharing and management, to support evidence-‐based decision making.
This presentation has been prepared with the objective to give readers a quick introduction to the Open Source GeoNode platform and its functionalities for the creation of a Spatial Data Infrastructure completely based on open Source components.
A new approach to spatial data infrastructure focused around users and collaboration. Development, Implementation and maintenance of a Geonode portal for local and regional collaboration, geospatial data sharing and management, to support evidence-‐based decision making.
This presentation has been prepared with the objective to give readers a quick introduction to the Open Source GeoNode platform and its functionalities for the creation of a Spatial Data Infrastructure completely based on open Source components.
Introduction to GIS - Basic spatial concepts - Coordinate Systems - GIS and Information Systems – Definitions – History of GIS - Components of a GIS – Hardware, Software, Data, People, Methods – Proprietary and open source Software - Types of data – Spatial, Attribute data- types of attributes – scales/ levels of measurements.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
Government has huge amounts of information but how can this be effectively managed and delivered through the web? This session will ‘lift the lid’ on web mapping technology and identify some of the key issues that must be addressed to achieve a successful outcome.
The NSW government SIX Viewer web mapping portal will be used as a case study to demonstrate how terabytes of data can be integrated and delivered via the Internet.
Talk about what relation between web and mapping. Also the process to create and collaborate on-line map using free source like mapserver, geoserver, postgis, openlayer.
Spatial Data Concepts: Introduction to GIS,
Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane
coordinate systems, Vector data model, Raster data
model
Data Input and Geometric transformation: Existing
GIS data, Metadata, Conversion of existing data,
Creating new data, Geometric transformation, RMS
error and its interpretation, Resampling of pixel
values.
Attribute data input and data display : Attribute data in
GIS, Relational model, Data entry, Manipulation of
fields and attribute data, cartographic symbolization,
types of maps, typography, map design, map
production
Data exploration: Exploration, attribute data query,
spatial data query, raster data query, geographic
visualization
Vector data analysis: Introduction, buffering, map
overlay, Distance measurement and map manipulation.
Raster data analysis: Data analysis environment, local
operations, neighbourhood operations, zonal
operations, Distance measure operations.
Spatial Interpolation: Elements, Global methods, local
methods, Kriging, Comparisons of different methods
The presentation gives an overview of what metadata is and why it is important. It also addresses the benefits that metadata can bring and offers advice and tips on how to produce good quality metadata and, to close, how EUDAT uses metadata in the B2FIND service.
November 2016
Introduction to GIS - Basic spatial concepts - Coordinate Systems - GIS and Information Systems – Definitions – History of GIS - Components of a GIS – Hardware, Software, Data, People, Methods – Proprietary and open source Software - Types of data – Spatial, Attribute data- types of attributes – scales/ levels of measurements.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
Government has huge amounts of information but how can this be effectively managed and delivered through the web? This session will ‘lift the lid’ on web mapping technology and identify some of the key issues that must be addressed to achieve a successful outcome.
The NSW government SIX Viewer web mapping portal will be used as a case study to demonstrate how terabytes of data can be integrated and delivered via the Internet.
Talk about what relation between web and mapping. Also the process to create and collaborate on-line map using free source like mapserver, geoserver, postgis, openlayer.
Spatial Data Concepts: Introduction to GIS,
Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane
coordinate systems, Vector data model, Raster data
model
Data Input and Geometric transformation: Existing
GIS data, Metadata, Conversion of existing data,
Creating new data, Geometric transformation, RMS
error and its interpretation, Resampling of pixel
values.
Attribute data input and data display : Attribute data in
GIS, Relational model, Data entry, Manipulation of
fields and attribute data, cartographic symbolization,
types of maps, typography, map design, map
production
Data exploration: Exploration, attribute data query,
spatial data query, raster data query, geographic
visualization
Vector data analysis: Introduction, buffering, map
overlay, Distance measurement and map manipulation.
Raster data analysis: Data analysis environment, local
operations, neighbourhood operations, zonal
operations, Distance measure operations.
Spatial Interpolation: Elements, Global methods, local
methods, Kriging, Comparisons of different methods
The presentation gives an overview of what metadata is and why it is important. It also addresses the benefits that metadata can bring and offers advice and tips on how to produce good quality metadata and, to close, how EUDAT uses metadata in the B2FIND service.
November 2016
Presentatie Makx Dekkers tijdens mini-symposium 14 september 2006 in den Haag.
Makx Dekkers, de managing director van het succesvolle Dublin Core Metadata Initiative, ging uitgebreid in op de toepassingen van Dublin Core binnen overheden en het bedrijfsleven en de kernaspecten die een rol spelen bij de toepassing van deze standaard.
Bron: http://www.advies.overheid.nl/5581/
metadata & open source #osgeonl dag 2012 pvangenuchten
Een presentatie op osgeo nl dag Velp.
Data providers hebben afgelopen jaar (getriggered door open data, atlas vd leefomgeving en inspire) hard gewerkt om hun data en metadata online te krijgen. Nu is het de beurt aan de client-software om goed met de gebruikte jonge standaarden aan de gang te gaan om de data optimaal te ontsluiten. Enkele use-cases worden gepresenteerd hoe dit zou kunnen.
[dutch language] Slides bij een gastcollege over het gebruik van website-metadata bij zoekmachineoptimalisatie. Voor de Hogeschool van Amsterdam (HvA), Afdeling MIC (Media, informatie en Communicatie)
a brief overview and introduction to metadata from how it is used on the web (including seo and tagging) to its use in Flickr and library catalogs by robin fay, georgiawebgurl@gmail.com.
A presentation of the underlying motivations and institutional context behind GeoNode, some of its major design decisions, and unresolved challenges for its sustainability.
I gave this talk at UC Berkeley School of Information's research seminar on Information and Communication Technology for Development (ICTD).
Much of the material comes from an older presentation I wrote with Rolando Peñate.
This is a brief introduction to GeoNode. GeoNode is an Open-Source content management system. It is a web-based application for developing web-GIS and for deploying spatial data infrastructures (SDI). It is designed to be extended and modified and can be integrated into existing platforms.
David Coleman: Challenging Traditional Models, Roles and Responsibilities in ...GSDI Association
GSDI President, Dr David Coleman's presentation at the Joint International Conference onGeospatial Theory, Processing Modeling and ApplicationsToronto, 6 October 2014.
David Coleman presentation at SDI Summit 2014, Calgary, Canada, 17-19 Sept 2014GSDI Association
Keynote presentation at Pan-Canadian SDI Summit 2014 by GSDI Association President David Coleman entitled "International SDI Initiatives: Thinking Globally, Acting Locally”. After providing context on the role Canadians played in early land information networking and SDI developments through the 1980s and early 1990s, he described the importance of such transnational and international SDI initiatives as Digital Earth, GEO, OGC & ISO, UN GGIM and — with special emphasis on the GSDI Cookbook and Small Grants Program — the GSDI Association itself.
Advanced Analytics and Machine Learning with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3aXysas
Advanced data science techniques, like machine learning, have proven to be extremely useful to derive valuable insights from your data. Data Science platforms have become more approachable and user friendly. With all the advancements in the technology space, the Data Scientist is still spending most of the time massaging and manipulating the data into a usable data asset. How can we empower the data scientist? How can we make data more accessible, and foster a data sharing culture?
Join us, and we will show you how Data Virtualization can do just that, with an agile and AI/ML laced data management platform. It can empower your organization, foster a data sharing culture, and simplify the life of the data scientist.
Watch this webinar to learn:
- How data virtualization simplifies the life of the data scientist, by overcoming data access and manipulation hurdles.
- How integrated Denodo Data Science notebook provides for a unified environment
- How Denodo uses AI/ML internally to drive the value of the data and expose insights
- How customers have used Data Virtualization in their Data Science initiatives.
Simple APIs for Health Tracking - COVID CaseLuis Bermudez
Provides information about the architecture for a Health Spatial Data Infrastructure, example of a grassroots efforts Application Program Interface (API) to share COVID data, connected to an open source client MapStore hosted in Amazon S3.
Data has been around for a long time. But only in two formats ANALOG and DIGITAL. Recently at an ever increasing rate DIGITAL DATA is growing exponentially year over year. Understand the best practice in Data Integration.
The presentation will provide the architecture and tricks to make available a low cost simple mapping capability for a rich geospatial web dashboard that can be used to track COVID-19. The dashboard is based on the open source MapStore Framework https://github.com/geosolutions-it/MapStore2. It interacts with an external API, following a distributed web architecture principle, and it has been deployed in an Amazon S3 bucket (https://www.covidtrackingmap.com/).
Similar to Spatial Data Infrastructure Best Practices with GeoNode (20)
Context, Causality, and Information Flow: Implications for Privacy Engineerin...Sebastian Benthall
The creators of technical infrastructure are under social and legal pressure to comply with expectations that can be difficult to translate into computational and business logics. The dissertation presented in this talk bridges this gap through three projects that focus on privacy engineering, information security, and data economics, respectively. These projects culminate in a new formal method for evaluating the strategic and tactical value of data. This method relies on a core theoretical contribution building on the work of Shannon, Dretske, Pearl, Koller, and Nissenbaum: a definition of information flow as a channel situated in a context of causal relations.
I explore ways to combine complex network science with the Rubin model of conference inference. In broad strokes, I discuss the difference between exogenous shocks and endogenous process, and how granularity in time can be used to tease causality out of a complex system.
In networked publics, power based on network positionality replaces media power. How can we design networked publics to improve parity? I present @TheTweetserve, a prototype solution.
This presentation introduces the philosophical field of epistemology and the problem of skepticism. It then outlines Fred Dretske's response to the problem. Lastly, it argues that Dretske's use of information reduces to Shannon's 'mutual information'.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
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- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
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https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
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The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
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Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
3. “… the sources, systems, network linkages, standards, and institutional issues involved in delivering spatially-related data from many different sources to the widest possible group of potential users at affordable costs.” – Groot & McLaughlin 2000 Spatial Data Infrastructure (SDI)
4. The theory of SDI developed before we learned what was possible with the Internet
85. Open Data Optimism Features like User reputation Organizational endorsement Flexible security address data quality concerns
86. Open Data Optimism GeoNode supports the continuum of openness with a common platform for institutional GIS and neogeography
87. What about Features X,Y, Z? OpenGeo: We welcome your investment in new GeoNode features! Inquire at the OpenGeo Booth. (Also, patches are very welcome)
I’d like to talk a bit about SDI's. Specifically what I think is the last step in building the dream of INSPIRE. If we're to look at this one definition of SDI INSPIRE has already done most every thing needed - it's written in to law, there are standards, everyone's agreed and it's moving forward. But I have a worry:
Underlying all of this is our commitment to open source, as it is the reason for our success, and we want to spread it widely
Make the data findable on Google Maps, not just on catalogs Should be accessible on as many places as possible, not locked in to the portal We’re starting to do this with GeoServer, putting actual data on the map, but with links back to the important metadata for the whole dataset