Social Validation of INSPIRE Annex III Data Structures in EU Habitats (27th of June 16:00 room Fintry) Karel Charvat Help Service Remote Sensing

Content Lessons learn from user communities Why harmonize data? For whom are metadata important From INSPIRE to Habitats Architecture Reference laboratory as prove of concept Pilots testbeds

Lessons learn from user communities NATURAL RESOURCE MGMT ECO- TOURISM WILD SALMON MONITORING LA PALMA MARINE RESERVE NAT L POLICY HIKING TRIP PLANNER CZECH NAT L FOREST PROGRAMME SORIA NATURAL RESERVE SHEEP & GOAT HERD MANAGEMENT ECON ACTIVITY AT COASTAL BENTHIC HAB. ECONOMIC ACTIVITIES

Lessons learn from user communities Analysis of use cases Generalization How communities request could influence architecture design, data models and metadata requirements

Analysis of use cases Use case 1 Actors Task Sheep and Goat Herding Management Personnel at Madonie Park Authority This is mostly an internal but fundamental task at Madonie Park Authority the requires the availability of geospatial data inside the whole Office and for external consultants (mainly researchers) that must help internal staff in managing the areas of the park. All this people access data by their GIS software or the WEBGIS platform, through geospatial web services INSPIRE compliant. Assumptions The proprietary databases can be made INSPIRE-compliant using the HABITATS Metadata profile in order to be accessed through the Sicily Region Portal using GIS or WEBGIS software compliant to OGC web services. Description Comments People at Madonie Park Authority deal with the management of grazing areas in a sustainable way allowing shepherds to access to areas, assigned to each of them, for grazing of sheep and goats. The control of the impact of grazing on assigned areas is carried out by Park Authority Personnel and external experts. This requires also the production of new layers on the state of areas the must be in a format compliant to ISPIRE directive in order to be used in an appropriate way. Data used for this task are: - Grazing plan; - Animals position distributed over the whole period of grazing; - State of conservation of areas (this includes some information such as level of pressure caused by animals).

Analysis of use cases Use case Actors Task Wild Salmon Monitoring and Management Internationally Researchers, and Decision Makers The International SALSEA Group through collaboration in the FP7 SALSEA-Merge project is investigating and recording in 2 major databases, the migration and distribution of salmon in the North-East Atlantic. The Use Case is to make their extensive data open and accessible using INSPIRE principles. Based on their existing best-practice, this group is likely to impact on the proposed salmonrelated data, metadata and services that will be input to the INSPIRE TWGs. Assumptions As the SALSEA Group wish to focus all of their efforts on their scientific work until the end of the SALSEA Merge project, it will be late 2011 before they will allow their data to be made available to a HABITATS pilot. They also wish to see how the Irish National pilot gets on and reuse its learning and approach. Description Comments This group uses the widely used best-practice ICES WGNAPES database structure. WGNAPES is a permanent Group that will continue after the SALSEA-Merge project ends in 2011. ICES/WGNAPES is an Internal database composed of National databases. With some fields added for SALSEA-Merge and the Genetic database. So it is good practice and a permanent working group which should lead to very useful inputs to the 4 HABITATS INSPIRE themes. This case with SALSEA-Merge is complex, and touches on the potentially high commercial value of the genetic databases, which is the reason for the reticence of the scientists involved in opening up their information to be INSPIRE compliant. On the other hand, interfacing INSPIRE-compliant databases with commercial services might be the most effective means for them to profit from their research. These issues will be further explored when MAC is able to more actively engage with the SALSEA-Merge stakeholders, after their current project work ends.

Analysis of use cases Use case Actors Task Subsidies in the forest management forest owners, state and regional forest administration, EU public Every time the forest owner decides to apply for one, or more of the subsidy programmes in forestry, he needs to prepare project of the desired action. The digital datasets of the Regional Plans of Forest Development (RPFD) can be used to plan the reforestation of the target tree species in respect with their natural conditions, to manage the decision process in case of windthrow event, to build the shelter, or the new biking trail, etc. Assumptions RPFD digital forest maps: - Typological map 1:10 000 - Map of forest altitudinal zones 1:50 000 - Map of forest target management sets 1:25 000 - Map of long-term forest protection measures 1:25 000 - Map of declared functions 1:25000 - Map of function potential 1:25 000 - Transportation map 1:25 000 Description In the Czech forest law, there are several means of promotion the sustainable forest management. The government provides subsidies for reforestation and plantations of native forest species, to support the wood production after natural disasters (bark beetle, windthrow events) and gentle management practices. Further there are subsidies to promote rural development and recreational function of forests (afforestation of agricultural land, building of biking trails and other tourist infrastructure, and more.) The information from the Regional Plans of Forest Development (RPFD) datasets serve as a basis the decision-making, project preparation, and finally also controls of the subsidies usage. Comments

Analysis of use cases data usage Regional data used regionally Global data used regionally Regional data used cross regionally Regional data used globally Global data used globally

Regional data used regionally There is not direct requirement for INSPIRE data models Local data models could be wider Local data models reflect regional needs and also regional decision processes If data are not shared outside of region (but in many cases it is necessary), in principle global standards are not needed Standards are needed in case of more data suppliers, to guarantee data consistence

Regional data used regionally

Global data used regionally Global data are in some content something like de facto standards In some cases it is necessary to be possible transform data into such models, which is required by regional decision processes The global model has to cover regional decision needs (GMES case for example) Question is, if this transformation will be done on fly or offline Language problem

Example FMI data used locally

Regional data used cross regionally There is already very visible problem of data harmonization, this problem is higher, in the case of cross boarder regions In many cases, like tourism we need deal not with one or more separate data theme, but with complex mixture of themes related to INSPIRE In some application cases model could be broader then INSPIRE definition Language problem

Tourist example

Regional data used globally Probably most relevant cases for INSPIRE data model The idea is to combine local data sets into one data set The regional data has to be transformed (in many cases simplified) into global model Relevant cases are tourism, transport, education, research, environment protection, risk management, strategic decision Language problem

Regional data used globally

Global data used globally Global data are standard or de facto standard. It is expected, that in the case of data of public sector, this data will be already in INSPIRE models It could happened, that this models has to be transformed on the base of needs of concrete application area. Transformation could be based also on Feature Encoding or SLD.

Global data used globally

Sea Regions Bio-geographical regions Habitats and biotopes Species distribution D3.1 Conceptual Data Models UML Class Diagrams Feature Catalogues INSPIRE TWGs methodology used for INSPIRE data specification, international standards As simple as possible Just common elements and attributes To enable an extension of models To interconnect Habitats themes To re-use existing componets TRAGSATEC analyses of data models for selected themes used in single countries participating on Habitats project results of previous tasks of Habitats project TU Graz HSRS INSPIRE testing IMCS

INSPIRE Data Specifications 2.0 FMI data Harmonization Testing of specifications (based on Habitats data models and user requirements) Sea Regions Bio-geographical regions Habitats and biotopes Species distribution

Source data Vegetation tiers (altitudinal vegetation zones) layer Part of PFD (Regional Plans of Forest Development) produced by FMI Spatial reference system - SJTSK (Czech national system) FMI original classification system

New Data Model Existing data model + referencehabitattypeid: CharacterString referencehabitattypescheme: ReferenceHabitatTypeSchemeValue localschemeuri: URI localnamevalue: CharacterString geometry: polygon referencehabitattypeid: eunis_value referencehabitattypescheme: eunis localschemeuri: link_to_fmi_classification localnamevalue: FMI_classification_value

Harmonization process Open SHP file and its scheme New data model Save final SHP file Reclassification FMI EUNIS

Taxonomy reclassification (FMI Eunis) 0 Pine G3.42,"4","Middle European [Pinus sylvestris] forests" 1 Oak G1.87,"4","Medio-European acidophilous [Quercus] forests" 2 Beech-oak G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests" 3 Oak-beech G1.82,"4","Atlantic acidophilous [Fagus] - [Quercus] forests" 4 Beech G1.6,"3","[Fagus] woodland" 5 Fir-beech G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland" 6 Spruce-beech G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland" 7 Beech-spruce G4.6,"3","Mixed [Abies] - [Picea] - [Fagus] woodland" 8 Spruce G3.1D,"4","Hercynian subalpine [Picea] forests" 9 Dwarp pine F2.45,"4","Hercynian [Pinus mugo] scrub"

Target data Source data (simplified)

Metadata profiles and cataloging Requirements on metadata information are growing with professionalism of users. Simply we can say, that for example tourist requirements will be done usually by theme of information and spatial or eventually time extend Requirements of specialist could lead to extension of current INSPIRE standards (done as part of Habitats work)

Simple metadata inside of viewer

Habitats multi search

INSPIRE versus Habitats architecture

What is missing from Habitats view INSPIRE architecture doesn t reflect needs of regions about data collection and updating INSPIRE architecture doesn t reflect needs of regions about metadata collection and updating In single Habitats pilot cases you don t need necessary full architecture Components of Habitats architecture could be localized on more places.

Example Metadata Habitats metadata management has to be divided into single components, guarantee communication using CSW standards. So metadata management system could run on different server, than single clients Metadata management system is divided from metadata edition and also from discovery services.

Example Metadata Catalogue system is now composed from independent components: Metadata catalogue Metadata editor client Metadata import client Metadata harvesting client Metadata valuator client Light discovery services client Full discovery services client

Example Metadata Currently solved problem is about metadata management, if to use metadata harvesting or provide multi search to multiple catalogue Second option could be combined with some methods of metadata caching The problems are with different usage of standards in INSPIRE and ISO, for example some GEOSS catalogues are not compatible with INSPIRE based catalogues

View services Current most popular technologies are based on clients technologies. It give us some advantage, but also could bring problems with browsers and some operations like coordinate transformation or printing Server part of client is necessary

View services

Additional services required Sensor Observation Services Data uploading Data composition forming Vectorisation of data Data download Support for mobile online and offline data collection Support for iframe or portlets to be possible integrate components with Web pages

Usage of iframe

Reference laboratory Habitats RL is designed and implemented as a virtual database. It integrates different technologies like GIS, multimedia, and virtual reality. Important part is integration of social networking tools supporting social assessment. These services are not implemented on the Habitats portal directly, but they are implemented as virtual services on different places in Europe.

Reference laboratory

Pilot implementation Not all pilots need to implement full architecture, subset of architecture is given by pilot needs Pilot implementation are based on common generic architecture principles, but they are free to use different components and platforms, this give possibilities for good testing of interoperability Pilot applications are validate by users, but also against RL

Thank you for your attention Karel Charvat Help Service Remote Sensing