On Reputation and Geospatial Information

An interesting article appeared this year entitled “Say goodbye to the information age, it’s all about reputation now”  in which Gloria Origgi , philosopher and senior researcher, states that “We are experiencing a fundamental paradigm shift in our relationship to knowledge. From the ‘information age’, we are moving towards the ‘reputation age’, in which information will have value only if it is already filtered, evaluated and commented upon by others. Seen in this light, reputation has become a central pillar of collective intelligence today.”

This observation struck me as in some ways obvious–we are increasingly being asked, and increasingly volunteer, our opinions on everything from what we’ve purchased to where we ate out last to our last airline flight.  And we increasingly base our own decisions on how a product or service is evaluated by others.  It is my observation that this deluge in surveys and opinion polls makes it more challenging for those of us in the research community to get responses for our own surveys.

But more importantly, in the GIS world, reputation is becoming another part of metadata, influencing our decision whether or not, and how, to use a particular data item.   Does the number of “views” that a certain data item has had in a web GIS platform such as ArcGIS Online influence your decision?  Should it?  Along these lines, Gloria goes on to say that “Whenever we are at the point of accepting or rejecting new information, we should ask ourselves: Where does it come from? Does the source have a good reputation? Who are the authorities who believe it? What are my reasons for deferring to these authorities?”  I regularly encourage my students and colleagues to pay attention to the profile, or identification, of a data producer in ArcGIS Online or in any cloud based, crowd-sourced library.  If a data set looks rigorous and complete, but the author has not even bothered to change the “head and shoulders” outline or to populate the least bit of information about themselves, it casts doubt on whether I should trust that data set.

But Gloria’s observation also struck me as somewhat disturbing, because it touches on some core themes that we have been writing about in this blog for many years now:  How can we trust a geospatial data set, particularly in our web-based GIS environment?  In the days of “authoritative sources only”, when all we had to choose from was TIGER, Landsat, EOSAT, DLG, Land Use Land Cover, DEMs, digital orthophotos, and some other core data sets from mapping and statistical agencies, we still needed to evaluate data sources, lineage, quality, scale, date, methods, and other attributes, but making decisions has become more complex with modern web-based GIS libraries.  The reason is partly because we have much more data at our fingertips, much of it being crowdsourced. But the situation is more complex I believe because the expectation that data searching should be easy nowadays, because there is “so much out there,” and consequently, analysts feel pressure to keep the data access and manipulation part of a GIS project as short as possible, with perhaps too little attention on wise choices about data.

Another reason this makes me uneasy is, what happens if we are only paying attention to who likes a data set or who has viewed a data set, and paying less attention to other measures?  Just because a song is popular does not mean it is “good” according to one’s own measure of music quality.  And just because a data set is popular does not mean it is the best representation of a phenomenon one is seeking to understand.  A less popular data set might be the most suitable.

What are your reactions to the impact that reputation and popularity are having or could have on the field of GIS?

Decisions, decisions… To what extent do we or should we use reputation and popularity in our choices of data to use?