Countryside Council for Wales

Coastal and Marine Resource Atlas

Final Report

August 2006

It is important to note that the digital atlas is not intended to substitute the provision of environmental advice during incident response. In an emergency response operation all reasonable efforts should be made to contact statutory bodies for advice on a case-by-case, incident-by-incident basis. Coastal and Marine Resource Atlas - Final Report

Executive Summary

This project entitled ‘Coastal and Marine Resource Atlas’ had a remit to produce a new digital atlas of habitats and species in marine and coastal areas of Britain. This represents a complete revision to the hardcopy atlas produced in the early 1990s. The project was managed by the Maritime and Coastguard Agency (MCA) and a steering group representing a wide range of project partners involved in oil spill contingency planning and response.

The project has delivered a digital ‘Coastal and Marine Resource Atlas’ and, critically, a sustainable mechanism by which the atlas will be maintained and updated, ensuring that it remains accurate and fit for purpose.

The atlas has been updated using a list of priority datasets describing important coastal and marine habitats and species, as well as physical geography and relevant infrastructure. This key information will meet the needs of operational staff involved in contingency planning, pollution incident response and clean up. The atlas will also act as a resource for a wider audience of environmental professionals and researchers.

The atlas is hosted as a sub-topic on the Defra MAGIC (Multi-Agency Geographic Information for the Countryside) website. MAGIC is an ideal host for the atlas because it is already widely known and used by environmental professionals, has an expert data management team in place, and conforms to good practice in the management of geographical information.

This final report defines the objectives behind the project, outlines the two-phase process by which the atlas was constructed, and describes its constituent datasets and method of dissemination. It identifies how the resource will be maintained and summarises problems that were encountered during course of the project. Recommendations, based on project experiences, are put forward.

For those interested in the data content and management processes, this report should to be read in conjunction with the Data Management Plan, a separate document that provides a procedural guide to data related processes that have been undertaken to compile the atlas, and which specifies responsibilities and processes for maintaining the data.

It is important to note that the digital atlas is not intended to substitute the provision of environmental advice during incident response. In an emergency response operation all reasonable efforts should be made to contact statutory bodies for advice on a case-by-case, incident-by-incident basis.

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Contents

1 Introduction……………………………………….………………………….....….3 1.1 Funding Partners…………………………………………………………….…… 3 1.2 Contractors……………………………………………………………….……….. ..4 1.3 Target Audience……………………………………………………………….…. 4

2 Phase I……………………………………………………………………………….6 2.1 Identifying priority datasets……………………………………..………….…....…6 2.2 Identifying a strategy for sustainable management of the atlas...... 6 2.3 Data licensing issues………………………………………………..…………...... 6 2.4 Data display issues………………………………………………………….….…...6

3 Phase II……………………………………………………………………….….....8 3.1 Collation and processing of datasets……………………….…………………....8 3.1.1 Problems encountered………………..…………………………………..10 3.2 Development of a broad scale marine & coastal resource database………..11 3.3 Development of a web-based application for stakeholder consultation……..11 3.4 Transfer of all necessary data and application files to Defra GI Team…...... 12

4 Datasets……………………………………………………………………………13 4.1 Datasets included in the Digital Atlas………………………………….………. 16 4.2 Datasets held by MAGIC to be included in the Atlas……………………...... 18 4.3 Datasets not included in the Atlas at present…………………….……….. 18

5 Dissemination of the Digital Atlas…………………………………………….20 5.1 MAGIC website………………………………………………………………...... 20

6 Data Management and Quality Assurance…………………………………..22 6.1 Metadata…………………………………………………………...... …….22 6.2 Data management plan……………………………………………….…..………22 6.3 Data update frequency……………………………………………………..……..23

7 Future Additions to the Atlas……………………………………………...... 24 7.1 Datasets………………………………………………………………………...... 24 7.2 MAGIC functionality...... 25

8 Recommendations………………………………………………………...…….26 8.1 Consistent data capture methodologies and strategies……………….………26 8.2 Improved data analysis and presentation…………………………………...... 27 8.3 Improved data and knowledge management…………..……………………….27 8.4 Improved publication strategies………………………………………………….28

Appendices

Appendix 1 List of datasets and their origins………………………………………… .29 Appendix 2 Defra Terms and Conditions for the use of data………………….……...31 Appendix 3 Metadata form definitions…………………………………..…………...... 32 Appendix 4 Creation of MAGIC compliant datasets…………………………………...34

List of Figures

Figure 1 Example of spatial distortion…………………………………………………….7 Figure 2 Data provision flow chart………………………………………………………..9 Figure 3 Coastal and Marine Resource Atlas hosted on MAGIC……………………..21

1 Introduction

Under the National Contingency Plan for Marine Pollution from Shipping and Offshore Installations, established Environment Groups must advise on the environmental aspects and impacts of any pollution response operations. In the early 1990s the Nature Conservancy Council (NCC), British Petroleum (BP) and the Marine Pollution Control Unit (MPCU) published a hardcopy atlas covering Great Britain (Atlas of Nature Conservation Sites in Great Britain Sensitive to Oil Pollution, produced for the Marine Pollution Control Unit, Department of Transport with support from BP plc, by the Nature Conservancy Council, Peterborough. © NCC 1991) principally to provide an audit of sensitive environmental habitats and species in the coastal zone and further offshore. The focus of the atlas was on oil spill contingency planning and these hardcopy maps provided an important tool used to inform advice by illustrating coastal environmental sensitivity. A partnership of organisations, lead by the Maritime and Coastguard Agency (MCA) decided that this atlas had become outdated and was in need of revision.

The purpose of this project, “Coastal and Marine Resource Atlas” was to revise the existing the Nature Conservation Sensitivity Maps by developing a digital database and sustainable update process. The key project objective was to deliver a digital coastal and marine resource atlas, which will provide a more flexible resource for oil spill contingency planning. It can be managed and updated more regularly and at lower costs than updating maps in a hardcopy format. The GIS-based tools used to disseminate the atlas are designed to help identify the environmental risk posed by a pollution incident and effectively manage the level of response required.

The project was split into two phases. The objective of Phase I, which commenced in Summer 2003, was to review the feasibility of producing a digital atlas by identifying relevant datasets and liasing with data providers to determine what information was available and in what format. Phase I identified a list of priority datasets for inclusion in the atlas and consultations confirmed that most of these were available as digital files suitable for import into GIS. A Phase 1 final report was produced in January of 2004. That report is appended to this final report.

Phase II took the project forward by collecting relevant datasets and building the digital atlas. The web-based atlas was a collaborative effort with Defra, through their GI Unit and using their existing MAGIC application framework. This final report provides a summary of the project, identifies options for the future expansion of the atlas and makes recommendations for the management of ecological datasets based on problems encountered.

1.1 Funding Partners

Funding partners involved in the realisation of this project are:

 Maritime and Coastguard Agency (MCA)  Department of Environment, Food and Rural Affairs (Defra)  Scottish Executive (SE)  Scottish Natural Heritage (SNH)  Energy Institute (EI)  Joint Nature Conservation Committee (JNCC)  Environment Agency (EA)  English Nature (EN)

 Department of Trade and Industry (DTI)  Hampshire County Council (HCC)  Essex County Council (ECC)  Kent County Council (KCC)

Although not a funding partner, the Countryside Council for Wales (CCW) also contributed significantly to project development.

At the outset it was the intention of the MCA and project partners to include the marine and coastal waters of Northern Ireland in the project. However, consultation with the Ordnance Survey of Northern Ireland identified technical and licensing problems with the use of OS background mapping data. In addition to this, the Department of the Environment Northern Ireland was already involved with a similar initiative, namely the EROCIPS (Emergency Response to Oil, Chemical and Inert Pollution from Shipping) project. For these reasons, it was decided that Northern Ireland would not be included in the project at present.

Similarly, it was agreed that the geographical coverage of the Atlas would not currently include the Isle of Man or Channel Islands. The Channel Islands Government have expressed interest in the project and requested that they be kept informed of developments so that their future inclusion would be possible.

1.2 Contractors

The following companies were contracted to deliver a digital atlas under the remit of this project:

 Oakwood Environmental Ltd Oakwood were hired to manage the project, and to lead on all liaison and data collection.

 GeoWise Ltd GeoWise were subcontracted to lead the technical development requirements of the project.

The implementation and on-going support of the web application has, and will continue to, benefit greatly from the work of the Defra GI Unit. Their commitment to the project at the start of Phase 2 has been of huge benefit to all project stakeholders and ensured that a sustainable platform could be provided for supporting implementation.

1.3 Target Audience

The digital atlas is primarily a tool aimed at supporting government agencies involved in environmental planning and in particular oil spill contingency planning and response. As a secondary function it will be of use to specialist information professionals working in the area of coastal and marine environmental management in the private, public and voluntary sectors. Its public availability through the MAGIC website will mean that other users such as politicians, pressure groups, educators, students and the general public will be able to access the information. The site will be aimed primarily at professionals, but open to a wider user community.

Information collected as part of this project is likely to be of benefit to marine and coastal planners and operational staff conducting the following functions:

1. Audit and planning – collating relevant datasets and allowing effective maritime pollution contingency plans to be drawn up in a consistent manner over large areas.

2. Operational response at time of oil spill - meeting the urgent needs of operational staff immediately on notification of a spill incident at any time of day or night.

3. Operational use for clean-up operations – meeting the less time-critical needs of operational staff in managing clean up operations effectively.

4. Assessment of damage and issues of responsibility – assessing the impact of a spill and producing detailed management reports.

5. Sharing coastal and marine resource data more widely – effective sharing of these data to all organisations involved in coastal management.

2 Phase I

2.1 Identifying priority datasets

Phase I of this project involved investigations to identify the priority datasets for inclusion in the digital atlas. Where possible attempts were also made to clarify the current availability, format, and licensing arrangements for the key information requirements (data layers) of the digital atlas. During this Phase the relevant data providers and research bodies currently undertaking coastal mapping in the UK were consulted. Discussions were held with data providers, including Ordnance Survey and UKHO/Metoc to understand licensing implications and how such a project could distribute data within agreed terms and conditions. A list of priority datasets to be included in the atlas was agreed (See Appendix 1).

 One important outcome of this consultation process was the discovery and development of the GB Coastal Morphology supplied by the British Geological Survey (BGS). This is an enhanced version of an existing BGS dataset, identified by the project team as the best option for mapping broad scale coastal morphology having explored and priced a range of different options.

2.2 Identifying a strategy for sustainable management of the atlas It was recognised that there had been many projects of this kind in the past all of which had produced a one-off set of data that could not be updated or maintained easily. Although many of the datasets to be included are relatively static, others are changing on a regular basis and must be updated to remain accurate.

It was felt that the Defra MAGIC Team could offer a sustainable platform on which to support a coastal and marine atlas on an on-going basis through the MAGIC website. Discussions were initiated with the Defra GI Team regarding the potential for applying the MAGIC infrastructure to this project and to determine how this could best be undertaken.

2.3 Data licensing issues There are a relatively complex set of licensing conditions attached to the use of some of the data, principally that supplied by commercial third parties like Ordnance Survey and the UK Hydrographic Office. These were explored in detail in Phase I including the use of OS derived data although issues were to continue to cause delays throughout the project as positions changed and data suppliers were unclear as to the status and implications of releasing their data for such a project.

Most data provided by government departments and agencies was of a non-sensitive nature and could be disseminated publicly in the form supplied. Thus, all data is viewable through the Defra MAGIC web site although only some of it is available to download.

2.4 Data display issues

Phase I also identified the problem of displaying coastal data and offshore data, mapped using different coordinate systems, together. Many of the problems of mapping coastal areas in the UK have been well documented through previous projects (see for example http://www.iczmap.com/). There are inconsistencies between Ordnance Survey methods for largely terrestrial mapping and Hydrographic

Office methods for largely marine charting relating to use of different coordinate systems, different datums and different map projections. Attempting to produce a single consistent map base to cover terrestrial, coastal and marine areas was one of the aims of the ICZMap Project although this was only done for a sample area near Southampton.

The number of display options was further reduced by the decision to use the existing MAGIC framework to host the atlas. Until the integration of this atlas, all of the data delivered through www.magic.gov.uk has been terrestrial and therefore the default projection system used has been based on Ordnance Survey British National Grid. Offshore data using this approach is increasingly distorted the further away it is from land (see Figure 1).

Figure 1. Example of spatial distortion that occurs when data is displayed outside of the bounds of a coordinate system. The figure shows oil and gas licensing blocks projected in a) a generic ED50 and b) the terrestrial GB system (British National Grid).

The Phase I process enabled Phase II to begin with clear options for the capture and presentation of key data layers and for the management and dissemination of information amongst the final users of the contingency planning tool.

3 Phase II

The key Phase II milestones necessary to achieve delivery of the final product were:

 Identification, collation, and processing of marine and coastal data sets;  The development of a broad-scale marine and coastal resource database;  Development of a web-based application for consultation on the atlas by all stake-holders;  Transfer of all necessary data and application files to Defra GI Team;  Production of a live on-line atlas based on the MAGIC infrastructure;  The production of a data management plan (DMP), outlining procedures and responsibilities for maintenance of the system; and  Production of the final report.

Throughout Phase II, Oakwood and GeoWise coordinated with the Defra GI Team to enable the MAGIC infrastructure to be reissued to include the Coastal and Marine Resource Atlas.

3.1 Collation and processing of datasets

Phase II involved the collation of data sets from various providers throughout England, Wales and Scotland. The process of data provision and their origins is illustrated in Figure 2. As would be expected when collating datasets from a range of sources, work was required to standardise them and to make them compliant with the digital atlas platform.

To help data providers supply their information in a useful manner a letter in June 2004 was circulated outlining the MAGIC data standards and formatting requirements for spatial data and its associated metadata (See Appendix 2). The letter included the following three documents providing specific direction and guidance:

 A step by step guide to data preparation (MAGIC Compliant Datasets.doc),  A spreadsheet for providing metadata (magic metadata template and example2.xls),  A document on the MAGIC data standard (magi0015.pdf) providing information for filling out the metadata spreadsheet.

It was hoped that this guidance would reduce the requirement for additional data processing work. Some data suppliers were very co-operative in terms of offering their time to undertake data processing. Others provided their data in its raw form, almost certainly because they did not have the resources to do more for this project.

In some cases problems were referred back to the data supplier with an explanation in order for corrections to be made and it to be re-supplied. Where organisations lacked the resources or expertise to process their data, problems were fixed by contractors and data passed back to suppliers.

Figure 2. Data Provision Flow Chart

3.1.1 Problems encountered

One of the objectives of Phase I of this project was to identify, in advance, potential problems, inconsistencies and gaps in available data. Despite this, during Phase II data collation a number of problems were encountered, such as:

 Poorly managed, inaccessible data. Some datasets existed only in hardcopy paper format drawn by hand, or information had not been mapped, but was instead referenced in an inconsistent manner to geographical coordinates or features. Although Phase I had identified that some digitizing work would be required, in some cases it was found that when data was received, its quality did not lend itself to accurate digital mapping.   Inconsistent data records within a single dataset. Some datasets had been collected over time using different coordinate referencing systems (OS grid references, ED50 and lat/long coordinates) and at different levels of spatial accuracy resulting in time consuming processing. Examples include Cetaceans, Harbour and Grey Seal Counts, and Oil and Gas Subsurface Infrastructure.

 Incomparable regional datasets. The data had not been collected with a view to its wider use in broad scale mapping projects, resulting in inconsistent survey methodologies in different areas producing incomparable data. This was the case for the regional capture of data for English Saltmarsh. The result was a loss to the project of valuable information. An alternative dataset is being sourced.

 Incomplete data coverage at a national level. This was the result of data capture at a regional level for specific projects. In the case of Saltmarsh in England, detailed regional datasets exist but they do not fit together to make a comprehensive dataset for the whole of England.

 Multiple datasets for the same type of data. For example Sand Dune and Machair distribution in Scotland was available as two different datasets, yet neither were considered to be a true, accurate reflection of reality. This took a considerable amount of time to process. Multiple datasets for Saline Lagoons and Saltmarsh in Scotland were also available. This reflects the fact that data is often captured for different projects using different methodologies, meaning that they cannot be combined. In such cases, it was necessary to use only the most appropriate dataset, or to include both for completeness.

 Incomparable national datasets. Different approaches to data classification, survey techniques and mapping existed between national agencies. This meant that seamless layers representing individual information themes could not be produced from the whole of Britain.

 Inconsistent data collection and classification between national agencies. Some key datasets exist in some areas but not in others, for example, Cliffs were available in Scotland and England but not Wales, Seagrass Beds and Nationally Important Intertidal Biotopes were available for Wales but not elsewhere. Even where data does exist across all 3 nations, it is generally not consistent in terms of the way it has been collected and

managed so that it cannot be joined it together. This made consistent mapping of key coastal habitats in areas like the Solway Firth and the Severn Estuary impossible. There is a significant lack of UK wide coordination for the capture and management of key coastal and marine datasets.

 High spatial resolution for broad-scale mapping purposes. Some datasets like designated boundaries and coastal morphology types were captured at very high spatial resolutions that far exceed that needed by projects of this kind - data suppliers do not have 'official generalised versions' of these datasets that would be very useful for broader scale work. This means third parties re-process the data which, while possible, does create ‘non-official’ versions. Government Departments have started to release spatial datasets at multiple resolutions to counter this problem.

 Incomplete information of the origins, quality, scale or appropriate use of datasets. At least half of the datasets did not have complete metadata records. Some datasets appear to have no clear data owner despite being relatively significant - examples include the 3 mile and 12 mile nautical limits that effectively had no metadata and therefore no information about how they were created and who owns them. It was therefore very difficult to identify who would be responsible for their maintenance - they effectively fall through the organisational gap.

These issues were on-going throughout the duration of the project and caused substantial delays. This was not helped by the significant turn around time taken when requesting data or data processing, which frequently ran into several weeks. This again reflects the partnership nature of the project and the lack of resources, time and expertise within some organisations.

It was not possible to anticipate many of these problems in advance. Phase I investigations were conducted through consultations with representatives from each contributing organisation. In almost all cases problems identified in Phase II were of a highly detailed nature and could not have been identified before individual datasets were collated, analyzed and assessed for quality and fitness for purpose. A detailed assessment of dataset suitability and data processing requirements, involving discussions with data managers and technicians with intimate knowledge of the datasets was not within the scope or budget of Phase I which focused on high level business requirements, priority datasets and technical options for delivery.

Appendix 3 of the Data Management Plan, which should be read in conjunction with this report, lists the additional processing required for each dataset in the atlas.

3.2 Development of a broad scale marine and coastal resource database

GeoWise developed a data store of all collected datasets using the ESRI desktop product ArcGIS. Data was checked and symbolized appropriately.

3.3 Development of a web-based application for stakeholder consultation

The database was then loaded into the ESRI web mapping server product ArcIMS and a demonstration project developed for viewing an initial beta version of the on- line atlas. Comments from consultees were incorporated, and presentation of the

of 37 Coastal and Marine Resource Atlas - Final Report data was finalised with project stakeholders at a series of meetings, in which pilot versions of the atlas were demonstrated.

In respect of the data display issues identified in Section 2.4, it was agreed that offshore datasets would be displayed using the MAGIC default coordinate system, British National Grid, despite the problem of spatial distortion with distance from the British mainland. However, there will be a ‘marine view’ option on the website to display specific datasets in a more appropriate ED50 coordinate system that will reduce the spatial distortion of features. To achieve this some datasets will be duplicated in both GB National Grid and ED50 projection systems.

3.4 Transfer of all necessary data and application files to Defra GI Team

The ArcIMS project (AXL) file was passed together with the data files to the Defra GI Team to incorporate into MAGIC. The MAGIC team undertook development of the MAGIC site to extend functionality of the application to support coastal and marine datasets. This was carried out through a proof-of-concept phase.

The MAGIC Team coordinated a final round of consultation on a draft version of the on-line atlas before it was launched. A more detailed account of the process of producing the digital atlas can be found in the Data Management Plan (DMP). This documents the data related processes that have been undertaken to compile the atlas products and specifies responsibilities and processes for maintaining the data.

4. Datasets

4.1 Datasets included in the Digital Atlas

 Bathymetry Bathymetry data was obtained through Defra including the 5, 10, 20 and 40m contours within the UK EEZ. It was supplied by the commercial supplier SeaZone.

 Dataset: 3-Mile Nautical Limit Provided by: Environment Agency (EA)

3 nautical mile buffer zone around the UK baseline. Very limited information is available about the origins of this dataset.

 12 Mile Nautical Limit This dataset was supplied by CEFAS. It is intended that this will be replaced with a UKHO version in the future.

 Dataset: Oil & Gas Infrastructure Provided by: Downloaded from the DEAL website

The Digital Energy Atlas (DEAL) is a web-based service that provides free information about UK offshore oil and gas exploration and production (www.ukdeal.co.uk). Information is sourced from the United Kingdom Offshore Operators Association (UKOOA), individual oil companies, the BGS and the DTI, mapped, and held on the DEAL database on ED50 datum; International 1924 spheroid. Five data layers representing different oil and gas related information themes were sourced from DEAL for this project. For each of these datasets, a British National Grid version was created for inclusion in the MCA digital atlas.

The five data themes include:

o Licence Blocks o Surface Infrastructure o Subsurface Infrastructure o Well Heads o Pipelines

 Dataset: Offshore Windfarms Provided by: The Crown Estate

This dataset provides information regarding the location of operational offshore wind farms at Scroby Sands, Great Yarmouth and North Hoyle, North Wales.

 Dataset: Coastal Shellfish Beds Provided by: The Centre for Environment Fisheries and Aquaculture Science (CEFAS)

This dataset contains information on the locations of bivalve mollusc harvesting area classification zones.

 Dataset: Aquaculture Sites (Scotland) Provided by: Fisheries Research Services Marine Laboratory, Aberdeen

This dataset provides the locations of all aquaculture sites (shellfish and finfish) that have to be monitored or recorded under fish health legislation, including inactive, deregistered and undeveloped sites, as well as research facilities.

 Dataset: Boundaries of Standing Approvals for Dispersants (England and Wales) Provided by: DEFRA

This dataset provides polygons representing standing approvals for the use of dispersants around the England and Wales in case of an oil spill. Digitised by Oakwood Environmental Ltd from paper charts. Metadata form also provided.

 Dataset: Boundaries of Standing Approvals for Dispersants (Scotland) Provided by: SEERAD

This dataset provides polygons representing standing approvals for the use of dispersants around Scotland in case of an oil spill. Digitised by Oakwood Environmental Ltd from coordinates. Metadata also provided.

 Dataset: Pollution Control Zone Provided by: United Kingdom Hydrographic Office (UKHO)

This dataset provides information on the extent of the UK pollution control zone.

 Dataset: Scottish Bathing Waters Provided by: The Scottish Executive

This Dataset provides information on the microbiological quality of both coastal and inland waters designated under the Bathing Waters Directive (76/160/EEC). Sampling of waters at each site is undertaken by the Scottish Environment Protection Agency between June and September each year and the data compiled for annual reporting purposes.

 Dataset: Nuclear Power Stations Provided by: British Energy

Information was obtained regarding the locations of nuclear power stations from British Nuclear Fuels and British Energy. This information was then digitised from OS 1:50000 base maps at Oakwood Environmental Ltd. Metadata also provided.

 Dataset: Coastal Habitats (Scotland) Provided by: Scottish Natural Heritage (SNH)

Saline Lagoons polygons: Provided by the Joint Nature Conservation Committee.

Saline Lagoon points: Data provided from a number of reports but based on the 1988 Landcover Survey of Scotland.

Coastal Vegetated Shingle points: Taken from various reports.

The following datasets are subsets of polygons digitised from the 1988 Landcover Survey of Scotland:

o Cliffs o Intertidal Flats Polygons o Maritime Grassland polygons o Saltmarsh polygons

Sand Dunes and Machair: Polygons digitised from National Field Survey of Scottish Sand Dune and Machair Habitats 1995-97.

This produced a very large dataset of sites all of which were classified by NVC mosaic types. All polygons within each specific site were amalgamated to provide a site extent polygon layer of manageable volume. This modified dataset was sent back to SNH.

Saltmarsh points: This dataset provides the locations of salt marshes and sand dunes derived from the Sand Dune Vegetation survey of Scotland.

These two sand dune datasets represent data captured using different methodologies. For this reason it was not possible to combine them at this time.

 Dataset: Coastal habitats (England) Provided by: English Nature (EN)

The following coastal habitat datasets for England are all derived from a draft GIS dataset developed as part of English Nature’s Habitat Inventories Project. The project describes the known occurrence of UK Biodiversity Action Plan habitats from various nationally available datasets.

o Saline Lagoon o Coastal Sand Dune o Coastal Vegetated Shingle o Maritime Cliff and Slope o Intertidal Mudflats

 Dataset: Coastal Habitats (Wales) Provided by: Countryside Council for Wales (CCW)

The following datasets provide information derived from the Countryside Council for Wales Phase 1 Intertidal Survey Biotope dataset and information digitised using Ordnance Survey 1:50,000 maps.

o Seagrass Beds

o Saline Lagoons o Sand Dunes o Saltmarsh o Nationally Important Intertidal Habitats

 Dataset: Intertidal Substrates (England & Scotland) Provided by: British Geological Survey (BGS)

This dataset provides an indicative interpretation of beach composition classification, which has been collated as a desk study. The data is intended to be representative in terms of location.

 Dataset: Intertidal Substrate (Wales) Provided by: Countryside Council for Wales (CCW)

For this dataset, biotope is used as a basis for substratum type, providing information on intertidal substrata derived from Phase 1 Intertidal Biotope type, or where that data does not exist inference from Ordnance Survey 1:50,000 base mapping.

 Dataset: Cetaceans Provided by: Sea Mammal Research Unit (SMRU)

This dataset contains information taken from the joint cetacean database, an amalgamation of sightings and associated search effort data spanning 20 years. A full description of data treatment is to be found in Reid, Evans and Northridge 2003 - Atlas of cetacean distribution in north-west European waters. Layers include Minke whales, harbour porpoise, common bottlenose dolphin, short-beaked common dolphin, white-beaked dolphin, and Atlantic white-sided dolphin.

The data required considerable processing (it was provided as an Excel spreadsheet with lower left and upper right lat/long coordinates of a grid), and thought as to how it should be displayed in this atlas.

 Dataset: Seal Haul Out & Pupping Sites Provided by: Sea Mammal Research Unit (SMRU)

This dataset provides information on Grey Seal Breeding Colonies recorded by direct observation. The list is not exhaustive as pups may be born on virtually any beach around the UK. However, the main colonies are represented.

 Dataset: Harbour and Grey Seal Counts Provided by: Sea Mammal Research Unit (SMRU)

This dataset provides information on the distribution of Harbour & Grey Seals in August recorded by direct observation and displayed as groups aggregated into 10km squares.

 Dataset: Waders & Wildfoul Provided by: British Trust for Ornithology

This dataset provides information from The Wetland Bird Survey Core Counts, monthly counts of non-breeding water birds carried out by volunteers. The aims of the scheme are to determine the numbers of non-breeding water birds in the Great Britain, their trends and the importance of individual sites for each species.

 Dataset: Seabird Nesting Counts Provided by: Joint Nature Conservation Committee (JNCC)

This dataset was received as a spreadsheet file, derived from the Seabird 2000 dataset. The Seabird 2000 dataset contains data from a full census of all of the breeding seabirds in Britain and Ireland. The data were gathered between the years 1999 and 2003 from both coastal and inland colonies. The main objectives of the survey were: to obtain distribution and population information for all 25 species of seabird that regularly breed in the UK and Ireland; to get baseline figures for those species that had been surveyed poorly up to now.

Most of the records are referenced as a point although some are lines defined by two points. All are lat/long coordinates. The fact that some are lines was ignored with just the initial (x,y) point used as a spatial reference to build a point file.

 Dataset: Seabirds (Colony & Vulnerability to Oil) Provided by: Joint Nature Conservation Committee (JNCC)

Seabird concentrations are especially vulnerable to oil pollution, and may become contaminated by oil wherever concentrations occur at sea, sometimes at considerable distance from the coast. This dataset highlights the most vulnerable aggregations for each month of the year in offshore waters based on their abundance in each statistical rectangle and their vulnerability to the effects of oil pollution. Because the distribution and abundance of seabirds changes throughout the year and between years, the appropriate monthly dataset should be used.

 Dataset: Sensitive Fish Areas Provided by: Fisheries Research Services Marine Laboratory, Aberdeen

This dataset provides information on areas in which seismic surveying is excluded on the basis of spawning fish stocks and spawning grounds, with precision based on ICES rectangles. It is not based on any individual species but several commercially important species with relatively well understood spawning distributions. Data is presented in monthly intervals to display sensitive areas at different times of the year.

4.2 Datasets held by MAGIC to be included in the Atlas

A number of datasets were already held by Defra on their MAGIC website, and were therefore incorporated directly into the resource atlas by Defra’s GI Unit.

 OS Basemapping

Defra have access to OS data at appropriate scales for Great Britain, most public sector organisations are able to use this data under the Pan Government Agreement.

 Bathing Waters (England & Wales) Data on bathing waters in England and Wales was already held by the Environment Agency in GIS format, and this was provided directly to Defra.

 Conservation Designations Statutory conservation designations (SSSI, SAC, SPA, NNR/MNR, RAMSAR, Heritage Coast and Biosphere) for England were already held within Defra’s GI data hub. Datasets for these designations were supplied for Scotland and Wales to meet the needs of the project.

4.3 Datasets not included in the Atlas at present

Coastal Habitat - Salt Marsh (England)

 English Nature provided a number of separate regional datasets for salt marsh. This posed problems as it was not possible to compile these regional datasets into one consistent national dataset because different survey methodologies, data classification and mapping techniques were used in different regions. Environment Agency also provided a saltmarsh dataset, however there are currently copyright issues surrounding the use of this data. The project partnership recognises the importance of this dataset and it is hoped that saltmarsh data will be included in the Atlas in the near future.

Coastal Habitats (Scotland) - Seagrass Beds

 This dataset was due to be provided by Scottish Natural Heritage. They have informed Oakwood that although some data for the locations of seagrass beds does exist, this data was not collected for the purpose of mapping seagrass beds and so may not be exhaustive. In addition, the data that is available does not exist as a single seagrass bed dataset, instead the locations of seagrass beds form parts of other more extensive surveys. It is for this reason that they are currently not able to provide data on the locations of seagrass beds for the atlas.

Scoter (Wales)

 CCW provided data displaying the main concentrations of Common Scoter in Wales, as summarised from CCW data (2000-2002). However, due to the fact that scoter are included in the GB wide waders and wildfowl data it was felt that it may be confusing to the user to also have scoter displayed separately. In addition, the data only covers Wales which may lead the user to believe that scoter are found only in Wales.

5 Dissemination of the Digital Atlas

5.1 MAGIC website

MAGIC is the first web-based interactive map to bring together information on key environmental schemes and designations in one place. MAGIC is a partnership project involving seven government organisations that have responsibilities for rural policy-making and management, and although it has been designed to meet the needs of the partner organisations, the facility is available to anyone over the Internet.

MAGIC makes use of standard GIS tools to allow people to view and query the available data. Users do not require specialist software and can access maps using a standard web browser. The information available in MAGIC has expanded considerably since its launch in July 2002. Originally the interactive map was designed to show only datasets for England as this was the area common to all the partners. Since the launch, feedback has demonstrated that information for Scotland, Wales and marine areas is also required, so MAGIC is widening its geographic extent with the purpose of meeting the needs of MAGIC partners with GB-wide interests (MAGIC website, www.magic.gov.uk).

The MAGIC website is an ideal host for the coastal and marine digital atlas. It is already used by environmental professionals, has an expert data management team in place, and conforms to best practice in storing and disseminating geographical information. The inclusion of this project will also help MAGIC to fulfil the requirement for English, Scottish and Welsh marine data. Figure 3 shows the digital atlas hosted on the MAGIC website.

of 37 Coastal and Marine Resource Atlas – Final Report

Figure 3. Coastal and Marine Resource Atlas hosted on MAGIC.

6 Data Management and Quality Assurance

6.1 Metadata

The use of metadata is good practice when producing or storing any dataset, but for a project that involves the collection, management, archiving and dissemination of a large volume and variety of data to others it is essential.

A simple definition of metadata is “data about data”, or more usefully, structured information about a resource. Metadata often includes information like dataset name, dataset originator, frequency of update, last update, and supplier contact. It may also have a brief description of the data. This information makes it easier to discover data that is useful to your needs. Additional information is often included that helps the user to understand how information should be used and displayed, what its limitations and accuracy are, and who has access rights to view a dataset. It will also explain codes and terminology included in the data that may not be understood by users other than the data producer.

The main delivery method for the Atlas will be web based hosted as a specific ‘sub- topic’ within Defra’s existing MAGIC platform. Spatial data and associated metadata to be held in the Atlas must therefore meet the data standards adopted by MAGIC. To comply with these standards all data providers completed a standard MAGIC metadata form (See Appendix 3). This consistent approach ensured that, as far as possible, the key features of each data set were captured. This will in turn allow an ease of reference for future use and review and an established format for any data sets that may be added to the project in the future.

Unfortunately, the metadata forms were completed to various standards ranging from completion of all fields to completion of very few. This reflects the inconsistencies of data management and quality assurance standards among data providers. Where formalised data management procedures are absent, critical information about the origin and quality of datasets is often lacking due to reliance on personal knowledge of data sets held by individuals in an organisation

6.2 Data management plan

To assist maintenance and sustainability of the Atlas the processes for sourcing, quality assurance and processing of each dataset should be simple and repeatable. A data management plan has been compiled, including metadata forms for each dataset, for use by any organisation that may have a role in maintaining the Atlas. For the foreseeable future this responsibility will lie with Defra, as the owners of MAGIC. The plan provides a clear procedural guide to maintaining the data sets formatted in a series of flow guides to illustrate each step required to produce the atlas, including data request, data receipt, QA procedures, data input and processing, and final QA.

6.3 Data update frequency

The previous 1990 UK Coastal Environmental Sensitivity Maps have become increasingly redundant because many of the datasets evolved and were not updated and because entirely new and relevant datasets have become available. The constituent datasets of this digital atlas will also require updating in the future.

However, the advantage of a digital platform and the data management procedures that have been put in place is that the atlas’ constituent datasets can be updated more regularly and at lower cost than updating maps in a hardcopy format.

Once data is loaded on to MAGIC, updates will follow the current MAGIC update procedures (See Appendix 4). Where datasets change regularly, MAGIC will seek to ensure that the data is updated on MAGIC more frequently. MAGIC will also try to ensure that datasets are synchronised with those shown on other websites. MAGIC updates its data on a monthly basis and data management of the component datasets from this project will fit into this regime. It is however recognised that an emergency situation could require new or updated datasets outside this normal regime.

7 Future Additions to the Atlas

7.1 Datasets

Although the Atlas provides comprehensive data coverage for both the biological and physical elements of the coast there still remain data and information gaps. These include:

 Migratory routes of fish species such as salmon At present, information is included in the atlas regarding sensitive fish areas - sites where spawning fish congregate and spawning sites occur. However there is considerable information on the migratory routes of important fish species such as Salmon and Trout, and given their commercial and conservation importance these resources should be included during future revisions.

 The locations of proposed Special Areas of Conservation (SACs) Although the atlas currently contains the locations of SACs, there are a number of proposed, potential and possible SACs which are not included on the atlas. Given that government policy is that proposed SACs (e.g. Severn, Dee) are to be treated as though they are fully designated, and that possible/potential SACs are likely to be designated in the future, these sites should be included.

 National Trust owned properties/sites The National Trust is Britain’s largest coastal landowner. In fact, nearly one in every ten miles of coastline in England, Wales and Northern Ireland is cared for by the National Trust. It may well be beneficial to include coastal National Trust property in the atlas.

 The location of major shipping lanes and identification of coastal areas at most risk Shipping lanes including types and tonnages would give an indication of the types of cargoes being transported and highlight areas of risk. The relationship between shipping traffic and the vulnerability of UK coastline has been explored to identify key areas at risk from oil spills during the MEHRA’s (Marine Environmental High Risk Area) exercise undertaken by DfT. This information, along with the location of the MEHRA’s themselves might usefully be incorporated.

 Places of Refuge

 Aerial Photography

 Advice on dispersant use

 Satellite images

 Coastal defence – areas of managed retreat

 Local resilience fora boundaries

 Cultural / historic data

7.2 MAGIC functionality

It is suggested that if the MAGIC platform had the additional capability to allow datasets to be grouped more logically into multiple hierarchical themes (and sub- themes) it would benefit the Atlas by enhancing the dissemination of information to users:

8 Recommendations

8.1 Consistent data capture methodologies and strategies

The application of datasets collected for one purpose to use for a different purpose is a universal and widely under-estimated problem. During the data collation phase of this project there were examples where good information had been collected on a regional basis for a specific purpose, but regional offices had used different data capture methodologies. This was the case for English Saltmarsh. Further examples of project-specific data capture methods resulted in more than one dataset being included covering the same area, as on the case Scottish Saline Lagoons and Scottish Saltmarsh. Because data was not collected consistently, it was not feasible to combine these datasets to produce a comprehensive national version.

Information derived from specific projects can have very limited generic value. This project has demonstrated that data capture is generally done for a specific purpose and little appears to have been published looking at the real consequences of the government's 'collect once, use many times' philosophy. Although it was felt at the inception of this project that many of the core datasets were 'ready and waiting', in reality projects such as this clearly demonstrate that unless the benefits of the greater good are considered at a very early stage in a data capture project, lower up-front costs lead to a 'collect once, use once' outcome.

 Organisations should employ guidelines to ensure consistency in the way knowledge is created. This will ensure that data is captured, managed, analysed and published in the most appropriate and consistent manner, and ensure its wider generic value. Recording comprehensive metadata information when a dataset is created and whenever it is modified and updated should be central to this process. When collecting ecological information in particular, organisations should also strive to be consistent in their survey methodology.

This problem was also apparent at a national level, and is demonstrated particularly well by the coastal habitat datasets used in the digital atlas. Because national agencies had collected information about the same ecological theme either at different scales or using differing methodologies, it was impossible to create a joined up map of Great Britain for many of the coastal habitats. Instead, separate datasets for England, Scotland and Wales were used. As a consequence more data layers were included in the digital atlas, making it less user friendly and perhaps more confusing than necessary.

In addition to inconsistent data capture methodologies, evidence also implied a lack of coordination in data acquisition programs and strategies between national agencies. Information was not available for all habitat types across England, Scotland and Wales (E.g. Seagrass beds, Cliffs, Vegetated shingle, Nationally Important Intertidal Habitats). This inconsistency between the data of national agencies is an extension a fragmented approach to data acquisition at regional level.

 A more ‘joined up’ approach to data capture is required between the devolved government agencies. In particular, English Nature, Scottish Natural Heritage and the Countryside Council for Wales should make efforts to better coordinate their data capture methodologies and programs, particularly in areas such as habitat mapping.

8.2 Improved data analysis and presentation

Very often decision-makers are presented with a wide range of complex datasets on which to base their decisions. At best this can be unhelpful, at worst it can lead to a culture of reliance purely on ‘professional judgement’ rather than scientific evidence.

It is beneficial not only to undertake audits of data resources and allow them to be searched and visualised easily, but also to use skilled information professionals to analyse them effectively and present them in a form that is meaningful for managers and policy-makers. In the US a National Oceanic and Atmospheric Administration (NOAA) model has been used for at least the last 10 years to produce cumulative indices of coastal sensitivity to oil spills and risk associated with coastal stretches. The methodology is consistent and applied to the whole US coastline. Detailed datasets are collected that allow this model to be put together and cumulative indexes to be built. This kind of sensitivity mapping was partially addressed by the MEHRA exercise in recent years, but lacked a sufficient depth of analysis.

It is recommended that a similar process be considered in the UK so that a strategic assessment of all coastal and marine resources can be undertaken and risks assessed. The current approach, based on collation and presentation of individual relevant datasets, does not easily lend itself to strategic planning and policy-based decision-making

8.3 Improved data and knowledge management

The frequent incomplete information about the origin and quality of datasets demonstrates that effective management of valuable data is a function that is critical even for small organisations.

Some datasets are managed by specialist departments rather than dedicated information units and whilst reports are generally kept, data is often not managed effectively, metadata is not captured or is mislaid, and value is lost.

 Organisations should have generic information and knowledge management teams and policies over internal data sharing to avoid a hoarding culture. These teams should include GI specialists. They should be responsible for managing all information for an organisation and policies governing its management and publication.

Although some organisations have invested in effective business processes and tools for data management, many others have not. In some cases this relates to the size of the organisation and the limited availability of resources to undertake this work.

 Data management teams should undertake data audits to identifying gaps in their information holdings, and priorities for meeting operational and policy requirements. This exercise would include consultation with partner organisations to ensure a consistent, joined up approach.

 Where small organisations lack the resources to manage their data effectively, formal links should be made with partner organisations to work closely with them to provide additional expertise and resources. These relationships do exist, but they are often at a personal rather than formal

organisational level. Such a link between the Sea Mammal Research Unit and the JNCC would be beneficial.

Good Practice Case Study

The Phase 1 Intertidal datasets produced by the Countryside Council for Wales (CCW) was the most consistent and comprehensive available from any of the data providers. There appears to have been an organised and ‘joined up’ approach to data acquisition with the objective of producing a comprehensive geographical database of habitats and species for the whole of Wales. The survey methodology used to acquire information about the distribution of habitats and species was consistent and standardised between different surveys and regions. GIS files were provided with comprehensive metadata, indicating effective data management and publication strategies. This is in contrast to some of the work conducted by other agencies, which in some cases was fragmented and project specific. The programme of mapping work undertaken by CCW sets a benchmark standard for future data collection.

We would suggest that agencies across the UK follow this best practice by collating and managing key environmental datasets in a UK consistent and ongoing manner. One key dataset made available by CCW was Nationally Important Intertidal Habitats. Equivalent datasets for other parts of the UK would be valuable for sensitivity mapping and contingency planning. These would include: 1. Intertidal Habitats of National Importance 2. Marine Habitats of National Importance 3. Terrestrial Habitats of National Importance

8.4 Improved publication strategies

Research and data gathering projects often do not cost for the effective publication of data. In some cases this is because the technical infrastructure and channels of publication are not readily available. However, failing to effectively publish new data severely limits knowledge exchange and increases the risk of duplication. Creating an organisational, cultural and technical environment for effective knowledge management is a major undertaking but one that an increasing number of public sector organisations are attempting to do - see ODPM/IDeA initiatives like www.knowledgemanagement.org.uk.

A data-sharing framework would facilitate effective understanding and exchange of data between organisations that is currently lacking. The newly formed Marine Data Information Partnership is actively considering many of these limitations – Defra is a key player in this initiative. The MAGIC project is itself developing into a ‘one stop shop’ for national environmental data, encouraging knowledge exchange and effective data management. By hosting the Coastal and Marine Resource Atlas, value has been added to this project and the MAGIC initiative.

Appendix 1

List of datasets and their origins

Data Category Layer Theme Data Provider OS Basemapping Ordnance Survey

3 Mile Nautical Limit Environment Agency

12 Mile Nautical Limit CEFAS

Bathymetry Seazone Human Environment Licence blocks Surface infrastructure Oil & Gas Infrastructure Subsurface infrastructure DEAL website (BGS) Well heads Pipelines

Offshore Windfarms The Crown Estate

Classified bivalve mollusc Coastal Shellfish Beds harvesting areas (England and CEFAS Wales)

Fishfarms and Shellfish Farms FRS

Standing Approvals for Dispersants DEFRA - England and Wales

Standing Approvals for Dispersants SEERAD - Scotland

Pollution Control Zone UKHO

Bathing Waters – Environment Agency England & Wales

Bathing Waters - Scotland Scottish Executive

Environment Agency Nuclear Power Stations British Energy Conservation Designations SACs EN, CCW, SNH SPAs EN, CCW, SNH SSSIs EN, CCW, SNH NNRs EN, CCW, SNH RAMSARs EN, CCW, SNH Biosphere EN & CCW

Data Category Layer Theme Data Provider MNRs EN, CCW, SNH Natural Environment Saline Lagoons polygons JNCC on behalf of SEPA Saline Lagoon points Sand Dunes and Machair Saltmarsh points Coastal Habitats - Scotland Saltmarsh polygons SNH Coastal Vegetated Shingle points Cliffs Intertidal Flats Polygons Maritime Grassland polygons Saline Lagoon Coastal Sand Dune Coastal Habitats - England Coastal Vegetated Shingle English Nature Maritime Cliff and Slope Intertidal Mudflats Seagrass Beds Saline Lagoons Sand Dunes Coastal Habitats – Wales CCW Saltmarsh Nationally Important Intertidal Habitats Intertidal Substrates - England & BGS / DEFRA Scotland

Intertidal Substrates - Wales CCW Minke Whales Harbour Porpoise Common Bottlenose Dolphin SMRU Cetaceans Short-Beaked Common Dolphin JNCC White-beaked Dolphin Atlantic White-sided dolphin

Grey seal breeding colonies SMRU Seals JNCC Harbour and Grey Seal counts (August 1996-7) Spring Mean peak (April-June) Waders & Wildfowl Autumn Mean peak (July-Oct) BTO Winter Mean Peak (Nov-March) Seabird nesting counts

Seabirds Vulnerable concentrations to oil spills (Monthly, January to JNCC December) Sensitive Fish Areas Monthly, January to December MarLab

Appendix 2

Defra Terms and Conditions for the use of data

28 June 2004

Coastal & Marine Resources Digital Atlas for Contingency Planning –

As discussed in our conversation earlier this week, Oakwood has been awarded Phase II of the Coastal & marine Resources Digital Atlas contract by the Maritime and Coastguard Agency (MCA) and work to collate datasets for the digital coastal and marine resources atlas is now able to commence. Therefore, I am writing to provide further information that will assist you in providing your data to this project.

One of the delivery channels for the Atlas will be a web based atlas hosted as a specific ‘sub-topic’ through DEFRA’s existing online mapping initiative; MAGIC. Data standards for spatial data and it’s associated metadata that will be held in the Atlas therefore need to meet those currently employed under the MAGIC initiative.

To assist you in providing the required standards for your data please find attached the following documentation outlining the standards currently used by DEFRA under the MAGIC initiative;  step by step guide to data preparation (MAGIC Compliant Datasets.doc),  spreadsheet for providing metadata (magic metadata template and example2.xls),  document on the MAGIC data standard (magi0015.pdf) providing information for filling out the metadata spreadsheet.

It is essential for the ongoing success of this Atlas that the processes for sourcing, quality assurance and processing of each data set are simple and repeatable. Any processes to be undertaken by the data provider in providing the information will need to be documented so that they can be incorporated within a final Data Management Plan (DMP). Therefore to enable the sustainability of the Atlas, it is critical that data providers also provide information detailing the procedure in preparation of data so that future updates can be replicated successfully.

In order to deliver within the project schedule for the digital Atlas we will need to have collated all data sets and associated metadata from the data providers by the end of August 2004.

If you have any queries regarding the data standards or any other issues regarding provision of data to this project please do not hesitate to contact myself at the office. In the meantime on behalf of the MCA, DEFRA and other project funding groups, I would like to thank you for your assistance in this project.

Yours sincerely

Project Consultant

Appendix 3

Metadata form definitions table 3a Name Name of the dataset

Theme Defining characteristic Labelling convention Description of the geographic references used Definition The way in which geographic referencing object instances are defined Domain of use Geographic area within which the object type occurs Owner Name of organisation able to create and maintain Version number Serial number incremented by one each time a new version is created* Version date Date of creation of this version of the object Parent Name of a geographic referencing object type of which this is a sub- division Child Name of a geographic referencing object type which is a sub-division of this one table 3b Responsible authority Name of authority responsible for capture, maintenance and supply of data set to MAGIC Last update date Date that the data set was last updated Frequency of supply How often the data set is to be supplied in an updated format to MAGIC Version number Serial number incremented by one each time a new version is provided for the MAGIC application* Source Description Source of the data representing the boundary Scale Basic scale of data capture Data capture process Process used to capture the data Quality Details of quality assurance regime Symbology Symbology used to display data set Scale threshold Minimum scale at which the data should be displayed in MAGIC minimum Scale threshold Maximum scale at which the data should be displayed in MAGIC maximum Positional accuracy Positional accuracy of digitised feature Precision Precision of co-ordinates Measurement Type of measurement for features Unit of measurement Unit of measurement used for features Dimension Nature of the measurement provided for each feature (area or length)

Table 4a Element Name Element Identifier Element Definition Unique reference code Ref code Unique reference code supplied by the Responsible Authority for each feature Feature name Name Name or description of the feature Measurement Measure Area or linear measurement of the feature Designation date Date Date the site was designated Hotlink Hotlink to information about the Hotlink attribute

Table 4b Unique reference code Feature name

Appendix 4

Creation of MAGIC compliant datasets

------Section 1 – New Datasets ------

Check for Duplicates and Overlaps

1. Check wherever possible for duplicates and overlaps including duplicate point data.

Note: Some datasets do have genuine duplicates and overlaps on them - if this is the case the MAGIC Data Manager should be informed.

Check Polygon Data

1. Check that excluded areas within polygons are voids unless there is an accompanying ‘island’ feature separately identified.

2. Multi-part polygons should be merged so they are represented by a single feature.

Check Point Data

1. If a database of grid references is being supplied for point data, there should be only one record for each required point. If there are 3 sets of grid references for a record and each set requires an individual point then there should be 3 records.

2. Ensure that point data only falls within England and that there are no centroids in the sea.

Check Attribute Data

1. Field names should not be longer than 10 characters as they will be truncated in ArcIMS - if they are then alias's must be supplied to the MAGIC data manager.

2. Check that field names will make sense to wider audience or again supply alias's to the MAGIC data manager.

3. Check that the dataset field headings meet the mandatory attribute structure of MAGIC data standard. Each dataset should have at least the following fields (as the first 3 fields) and each of these fields must be populated for each record:

Ref_code: unique reference code supplied by the responsible authority for each feature Name: name or description of the feature Measure: area or linear measurement of the feature

Note: Although we are saying that these attributes are mandatory, in reality there may not be a unique ref_code (e.g. for ESA tiers) or measure (if the supplying authority do not wish measurements to be shown for e.g. Landscape Typology where the boundaries are illustrative rather than definitive). We should however endeavour to include them wherever possible.

4. Avoid punctuation within attributes if possible

5. Remove any fields that contain no attribute data at all

6. Check for any missing attributes or any inconsistent attributes

7. If there are a large number of fields on the dataset inform the MAGIC Data Manager which ones they wish to be displayed on MAGIC. If possible strip down the number of fields supplied on the dataset. Lots of fields slow down the system!

8. Check any area fields to see if the area is spatial from extent of feature, or indicative only or legally specified etc. Do this by adding a new field and calculating the area of the polygon. By comparing the 2 figures it is possible to get an indication of the type of measurement. Investigate and resolve any obvious anomalies.

9. Check the number of decimal places in any numeric fields – there should be no more than 2 decimal places.

10. Add any hotlinks to the dataset and check that they work or let the Magic Data Manager know what hotlinks if any you would like used.

Complete Documentation

Complete documentation for each dataset. The documentation should be supplied on the standard Data Documentation spreadsheet. If the organisation holds textual information about the dataset in another format - the relevant items should be extracted and transferred to the standard spreadsheet and then any remaining empty fields should be populated. Use the data dictionaries if at all possible except where free text is required.

1. Each field on the Data Documentation spreadsheet should have an entry (this may mean putting 'not known'. In some instances (e.g. symbology and scale thresholds) it is not always necessary to include any information here as they are optional items - in which case put ‘Not applicable’.

2. Check the unit of measurement agrees with the dataset.

** NB Forward documentation along with the new dataset

------Section 2 – Updated Datasets ------

Check for Duplicates and Overlaps

Same as for new datasets.

Check Polygon Data

Check Point Data

Check Attribute Data

Same as for new datasets but also check the following:

1. Check that the field names are the same as on the previous file and that they appear in the same order.

2. Check the number of features – if less than the previous version investigates to see if this is correct.

Complete/Check Documentation

1. Amend documentation where necessary. The main thing to remember to alter is the Dataset reference date.

** NB Forward updated documentation along with the updated dataset