Best Practices in Spatial Data Management

By Jessica Krokowski

Organizations rely on location-based data to make critical decisions every day. In recent years, the volume of spatial data has grown exponentially - and now includes maps, demographic information, territory assignments, drive times and any record field that can be associated with an address or geocode.

In many ways, location has become the glue that allows organizations to make connections across disparate systems and data types. Consider the simple example of a cell tower. Geospatial data link potential tower sites to elevation, coverage areas, customer households, buildings and obstructions, land use plans, population distributions, tax jurisdictions, terrain and surface analysis, atmospheric conditions and real estate availability, to name a few.

Corporations and government agencies spend billions of dollars to create, update and maintain these geospatial data. In many cases, however, this information is impossible to find, difficult to access, and frequently incompatible across departmental boundaries. That's why so many organizations are starting to look at best practices in spatial data management.

The focus on spatial data management has recently become more critical for two reasons:

  • Heightened focus on expense management, given a sluggish economy
  • New regulatory requirements - particularly in the public sector

With recent budget cuts, government agencies, in particular, are under pressure to deliver high-value, easily accessible citizen services. Accurate, accessible spatial data make this possible by making it easy to link disparate data points such as population, environment, employment, development, healthcare, security and more. When red tape and redundant efforts are replaced by collaboration and cooperation, agencies can make these much-needed connections quickly and efficiently.

While such efforts are voluntary in the United States, the public sector in Europe must soon comply with all facets of the INSPIRE directive. The principles behind INSPIRE are simple: the geographic data necessary for good governance should be collected only once, readily accessible and in formats that are usable by a variety of users and applications. Under this directive, public authorities must:

  • Publish metadata about their geographic information
  • Make data available according to standard interoperable specifications
  • Offer services for metadata discovery, viewing, download and data transformation
  • Harmonize the conditions under which EU members supply data and services

Historically, sharing data between organizations has been difficult - but the need for better spatial data management has never been so important. Government agencies, for example, understand that a high percent of natural disasters in Europe involve flooding. With coastal populations doubling over the past few decades and assets within 500 meters of the coast valued at over 1,000 billion Euros or more, emergency response needs to be immediate and well executed. Spatial data - such as the location of gas lines, hospitals, evacuation routes, traffic conditions and flood zones - need to be findable and accessible.

While the INSPIRE mandate only applies to the public sector, corporations are also looking for ways to improve  spatial data management as a way to cut costs, eliminate waste, avoid duplicate efforts and improve customer service. In some ways, the real value of spatial data management is in understanding all of the data assets internally.

Metadata unlock the potential of your data
Simply put, metadata are information about data. Metadata are descriptive information about a particular dataset, object or resource, including how it is formatted, and when and by whom it was collected. An example of metadata about a street dataset might include information about the vintage, data sources, etc. The publishing of metadata aids potential data users in finding exactly what they need and understanding appropriate uses for it. A metadata repository also helps reduce duplication of data collection efforts and can help organizations avoid duplicate purchases of the same datasets.

All content or metadata do not have to be put into one place, into one system, one database or a single spatial data infrastructure. Consider your town's library: each library maintains a collection of books, and a search at any library catalog will return books in other libraries. If your request returns a book in your local library, you can find it via its index. If the book is in a remote library, there are typically services to request that the book be delivered to your local library. An interconnected network of services permits data searching (and potentially viewing and downloading of data) from multiple catalogs at once. This concept is sometimes referred to as cascading.

High quality metadata provide for a host of benefits, including the ability to:

  • Clearly define ownership (including copyrights) and responsibility for data
  • Increase the usage of established data assets by making it easy to identify, track and access what exists today
  • Reduce the risk of acquiring data twice
  • Coordinate data collection efforts that may take place in different parts of the organization
  • Identify data redundancy and opportunities to reduce maintenance costs
  • Reduced time to perform change impact analysis
  • Improve quality by creating metadata that help users determine the appropriate use and context of the data
  • Understand where overlaps exist across business areas
  • Make it easier for users to understand the relationships between complex datasets
  • Improve analysis regarding the access and usage of data - which makes it easier to develop business cases for data maintenance
  • Enable managers to make quicker and more confident decisions every day

Key considerations
When it comes to tools and technologies, data stewards, GIS and IT managers are focused on multiple requirements.

•    Automated bulk collection of metadata. Metadata make it possible to search electronic records - so information that once took 10 phone calls to track down can be identified quickly and efficiently. In some ways, metadata provide for a clearing house of information, where users can save considerable time and money.

With the right technology, you can "harvest" metadata from your existing data and automatically populate the appropriate fields. Today's leading solutions, for example, can examine data to capture the date modified, the geography covered and the scope of overall content. Configurable templates can apply the same values across a set of metadata records or the whole dataset. For example, the name of the organization may be the same for all records but different contact people may be assigned to different datasets. Overall, the goal is to automate as much of the metadata collection as possible.

•    On-going upkeep of metadata. Capturing metadata at the point of content creation - by individuals who understand the value of the information - helps ensure that catalog tags accurately reflect the data and how they can be used.

•    Deployment and management of services. The ability to deploy using OGC services including WMS, WFS and Tile Server services with little effort makes it easy to distribute data.

•    Simple interfaces. End users - including people who have no GIS expertise - need ways to search metadata catalogs from both inside and outside their organization.

While it takes some effort to implement a spatial data management effort, leading edge mapping and GIS tools can help streamline and automate this endeavor. When applications, such as PBBI's MapInfo Manager, have tools such as templates and the ability to harvest metadata they enable catalogs to be created more easily and quickly through a batch process.

Published Thursday, December 2nd, 2010

Written by Jessica Krokowski

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