Data Points

I was recently reviewing the US Department of Transportation's National Address Database schema and noticed that there are many fields to parse out individual components of a street name.  The proposed schema is based on the National Emergency Number Association (NENA) Civic Location Data Exchange Format (CLDXF).

I feel like this type of thinking is somewhat antiquated and might have been useful in the past for companies building free-text search engines (also known as type-ahead or auto-complete) in an effort to increase response times.  But now it feels like this level of parsing for a street name is completely ineffective. Don't get me wrong, I understand parsing out the house number from the street name, but I am not convinced of the benefit to parse individual components of the street name.

The proposed schema from NENA is directed at supporting one use case, the next generation of emergency response (NG9-1-1).  I am starting to see local governments requesting help from 3^rd party data vendors and GIS consultants to move their data to this format.  Here is one example that was recently posted to GISCafé: https://www.giscafe.com/nbc/articles/view_article.php?section=CorpNews&articleid=1721802 .  But I still am trying to figure out the benefit of this level of parsing for an emergency response use case.

Can anyone enlighten me?

I was recently reviewing the US Department of Transportation's National Address Database schema and noticed that there are many fields to parse out individual components of a street name.  The proposed schema is based on the National Emergency Number Association (NENA) Civic Location Data Exchange Format (CLDXF).

I feel like this type of thinking is somewhat antiquated and might have been useful in the past for companies building free-text search engines (also known as type-ahead or auto-complete) in an effort to increase response times.  But now it feels like this level of parsing for a street name is completely ineffective. Don't get me wrong, I understand parsing out the house number from the street name, but I am not convinced of the benefit to parse individual components of the street name.

The proposed schema from NENA is directed at supporting one use case, the next generation of emergency response (NG9-1-1).  I am starting to see local governments requesting help from 3^rd party data vendors and GIS consultants to move their data to this format.  Here is one example that was recently posted to GISCafé: https://www.giscafe.com/nbc/articles/view_article.php?section=CorpNews&articleid=1721802 .  But I still am trying to figure out the benefit of this level of parsing for an emergency response use case.

Can anyone enlighten me?

I was recently reviewing the US Department of Transportation's National Address Database schema and noticed that there are many fields to parse out individual components of a street name.  The proposed schema is based on the National Emergency Number Association (NENA) Civic Location Data Exchange Format (CLDXF).

I feel like this type of thinking is somewhat antiquated and might have been useful in the past for companies building free-text search engines (also known as type-ahead or auto-complete) in an effort to increase response times.  But now it feels like this level of parsing for a street name is completely ineffective. Don't get me wrong, I understand parsing out the house number from the street name, but I am not convinced of the benefit to parse individual components of the street name.

The proposed schema from NENA is directed at supporting one use case, the next generation of emergency response (NG9-1-1).  I am starting to see local governments requesting help from 3^rd party data vendors and GIS consultants to move their data to this format.  Here is one example that was recently posted to GISCafé: https://www.giscafe.com/nbc/articles/view_article.php?section=CorpNews&articleid=1721802 .  But I still am trying to figure out the benefit of this level of parsing for an emergency response use case.

Can anyone enlighten me?