Spatial Data Management

The principles behind spatial data management 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 these principles, data managers 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

Corporations are 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.

Next

Spatial Data Science

The principles behind spatial data management 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 these principles, data managers 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

Corporations are 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.

Next

Geographic Information Retrieval

GIR is concerned with improving the quality of geographically specific information retrieval with a focus on access to unstructured documents such as those found on the Web.

There are several aspects of GIR that need to be improved:

  • detecting geographical references.
  • toponym disambiguation.
  • indexing documents, both spatially and for keywords.
  • ranking documents, both spatially and for thematic content.

Next

Metadata Management

Why is Metadata Management an important aspect of good Data Governance?

To turn data into information assets requires that you not only consider data governance but also metadata management. Without a complete understanding of the data upon which an organization relies, decisions about how it should be managed and used for competitive advantage, internal business processes and regulatory compliance will be based more on instinct than on facts.

Next

Geodavic Inc.

Providing a wide range of expertise centred on the world of geospatial technologies

Artificial Intelligence

The use of AI within GIS leveraging machine learning and data analysis techniques to enhance spatial data interpretation, automate feature detection, and improve decision-making processes in geographic information systems.

GIS Architecture

Our process builds on your existing information technology (IT) infrastructure and provides specific recommendations for hardware and network solutions based on existing and projected business (user) needs.

Information Retrieval

Information retrieval is the process of searching, locating, and extracting relevant data or documents from large collections of information based on user queries or criteria.

Project Management

Bringing project management discipline to the planning, organizing, and overseeing resources and tasks to achieve Enterprise GIS capabilities within a defined scope, time, and budget.

Software Development

Software development is the process of designing, coding, testing, and maintaining applications or systems to meet specific user needs and functional requirements.

Spatial Databases

Using Oracle Spatial or PostgreSQL+Postgis as specialized database systems designed to store, manage, and query geographic and spatial data, enabling efficient analysis and visualization of spatial relationships and features.