Don't let good geoscience data go to waste

We’ve all been there. You know that somewhere in your home, you have an item that would be very useful to you right now, but you can’t remember where you last saw it. You rummage through drawers, in the back of closets, pull out storage bins and basically tear the place apart, to no avail. Even if you eventually find it, you’ve wasted an hour and left a mess everywhere.

Where did my data go?!

This same problem plays out every day at companies around the world. Someone knows that a file folder exists with valuable information that would help with a project but has no idea where to begin looking. There is no central repository and no way to find it except to go on a wild goose chase.

For geoscientists, engineers and researchers, this may happen when information was purchased on a particular geographical region years ago for a project that never came to fruition. Now, they are looking at the region again for a new project, and nobody knows where to find the existing information.

Unstructured and unfound data

Too often, a significant amount of a company’s data is siloed and unstructured. The information is there, but it’s difficult to find or incompatible. As a result, far too much time is spent on locating and formatting data. Even a thorough search might not turn up everything you need, leaving you with incomplete data, which can weaken analyses.

Unstructured data leads to the potential repurchasing of already owned data sets, less informed decision-making, duplication of work, and spending too much time searching and not enough time analyzing.

Many professionals have resigned themselves to the idea that this is how things are done — but it doesn’t have to be this way. New information tools and technologies have made it possible for data experts to gather this data and finally make it easily accessible and usable in their workflows.

How to make sense of your data

By applying domain expertise and smart algorithms, experts can index and organize a company’s data, extracting information from different file types at scale. This process involves a number of steps:

1. Geo-tag the data.

• ●

  Metadata (e.g., file size, author, date created, date modified, geolocation, etc) must be extracted and structured.

• ●

  Custom taxonomies are created to enrich and classify data.

2. Make the data searchable.

• ●

  “Normalize” the data, and ensure it is in file types that are actually searchable (e.g., RTF, CSV, GeoTiff).

3. Use a platform with both geospatial and text search.

• ●

  By following these steps, experts on Geofacets’ data management services team can make an organization’s data easily searchable alongside millions of maps, figures and tables from peer-reviewed geoscience publications. The data can also be used via customized plug-ins in popular industry tools like ESRI’s ArcMap and ArcGIS Pro.

Improve efficiency and outcomes

Rescuing your company’s data in this way means no more precious time wasted on exhausting searches. A single search can provide a complete picture so that you plan and execute projects more efficiently, improving overall ROI and outcomes for your organization.