Joe Lamantia.com

I was enjoy­ing some of the engag­ing car­tograms avail­able from Worldmap­per, when I real­ized tag clouds might have some strong par­al­lels with car­tograms. After a quick sub­sti­tu­tion exer­cise, I’ve come to believe tag clouds could be to lists of meta­data what car­tograms are to maps; attempted solu­tions to sim­i­lar visu­al­iza­tion prob­lems dri­ven by com­mon and his­tor­i­cally con­sis­tent infor­ma­tion needs.
Here’s the train of thought behind the anal­ogy. Car­tograms are the dis­torted but cap­ti­vat­ing maps that change the famil­iar shapes of places on a map to visu­ally show data about geo­graphic loca­tions. Car­tograms change the way loca­tions appear to make a point or com­mu­ni­cate rel­a­tive dif­fer­ences in the under­ly­ing data; for exam­ple, by mak­ing coun­tries with higher GDP (gross domes­tic prod­uct) big­ger, and those with lower GDP smaller. In the exam­ple below, Japan’s size is much larger than it’s geo­graphic area, because it’s GDP is so high (it’s the dark green blob on the far right, much larger than China or India), while Africa is nearly invis­i­ble.
Gross Domes­tic Prod­uct

Tag clouds pur­sue the same goal: to enhance our under­stand­ing by com­mu­ni­cat­ing con­tex­tual mean­ing through changes in the way a set of things are visu­al­ized, rely­ing addi­tional dimen­sions of infor­ma­tion to make con­text explicit. Where car­tograms change geo­graphic units, tag clouds change the dis­play of a list of labels (the end point of a chain of link­ages con­nect­ing con­cepts to focuses) to com­mu­ni­cate the seman­tic impor­tance or con­text of the under­ly­ing con­cepts shown in the list.
Visu­ally, the rela­tion­ship of clouds to lists is sim­i­lar to that of maps and car­tograms; com­pare these two ren­der­ings of the most pop­u­lar search terms recorded by nytimes.com, one a sim­ple list and the other a tag cloud.
List Ren­der­ing of Search Terms

Cloud Ren­der­ing of Search Terms

This expla­na­tion of car­tograms from Car­togram Cen­tral a site sup­ported by the U.S. Geo­log­i­cal Sur­vey and tional Cen­ter for Geo­graphic Infor­ma­tion and Analy­sis makes the par­al­lels clearer, in greater detail.
“A car­togram is a type of graphic that depicts attrib­utes of geo­graphic objects as the object’s area. Because a car­togram does not depict geo­graphic space, but rather changes the size of objects depend­ing on a cer­tain attribute, a car­togram is not a true map. Car­tograms vary on their degree in which geo­graphic space is changed; some appear very sim­i­lar to a map, how­ever some look noth­ing like a map at all.“
Now for the cut and paste. Sub­sti­tute ‘tag cloud’ for car­togram, ‘seman­tic’ for geo­graphic, and ‘list’ in for map, and the same expla­na­tion reads:
“A tag cloud is a type of graphic that depicts attrib­utes of seman­tic objects as the object’s area. Because a tag cloud does not depict seman­tic space, but rather changes the size of objects depend­ing on a cer­tain attribute, a tag cloud is not a true list. Tag Clouds vary on their degree in which seman­tic space is changed; some appear very sim­i­lar to a list, how­ever some look noth­ing like a list at all.“
This is a good match for the cur­rent under­stand­ing of tag clouds.
Div­ing in deeper, Car­togram Cen­tral offers an excerpt from Car­tog­ra­phy: The­matic Map Design, that goes into more detail about the spe­cific char­ac­ter­is­tics of car­tograms.
Erwin Raisz called car­tograms ‘dia­gram­matic maps.’ Today they might be called car­tograms, value-by-area maps, anamor­phated images or sim­ply spa­tial trans­for­ma­tions. What­ever their name, car­tograms are unique rep­re­sen­ta­tions of geo­graph­i­cal space. Exam­ined more closely, the value-by-area map­ping tech­nique encodes the mapped data in a sim­ple and effi­cient man­ner with no data gen­er­al­iza­tion or loss of detail. Two forms, con­tigu­ous and non-contiguous, have become pop­u­lar. Map­ping require­ments include the preser­va­tion of shape, ori­en­ta­tion con­ti­gu­ity, and data that have suit­able vari­a­tion. Suc­cess­ful com­mu­ni­ca­tion depends on how well the map reader rec­og­nizes the shapes of the inter­nal enu­mer­a­tion units, the accu­racy of esti­mat­ing these areas, and effec­tive leg­end design. Com­plex forms include the two-variable map. Car­togram con­struc­tion may be by man­ual or com­puter means. In either method, a care­ful exam­i­na­tion of the logic behind the use of the car­togram must first be under­taken.“
Doing the same sub­sti­tu­tion exer­cise on this excerpt with the addi­tion of ‘rel­e­vance’ for value, ‘size’ for area, and ‘term’ for shape, yields sim­i­lar results:
“Erwin Raisz called tag clouds ‘dia­gram­matic lists.’ Today they might be called tag clouds, relevance-by-size lists, anamor­phated images or sim­ply spa­tial trans­for­ma­tions. What­ever their name, tag clouds are unique rep­re­sen­ta­tions of seman­tic space. Exam­ined more closely, the relevance-by-size list­ing tech­nique encodes the listed data in a sim­ple and effi­cient man­ner with no data gen­er­al­iza­tion or loss of detail. Two forms, con­tigu­ous and non-contiguous, have become pop­u­lar. List­ing require­ments include the preser­va­tion of term, ori­en­ta­tion, con­ti­gu­ity, and data that have suit­able vari­a­tion. Suc­cess­ful com­mu­ni­ca­tion depends on how well the list reader rec­og­nizes the terms (of the inter­nal enu­mer­a­tion units), the accu­racy of esti­mat­ing these sizes, and effec­tive leg­end design. Com­plex forms include the two-variable list. Tag cloud con­struc­tion may be by man­ual or com­puter means. In either method, a care­ful exam­i­na­tion of the logic behind the use of the tag cloud must first be under­taken.“
The cor­re­spon­dence here is strong as well.
Sta­ble Need
The fact that car­tograms and tag clouds show close par­al­lels means that while the tag cloud may be a new user inter­face ele­ment emerg­ing for the Web (and major desk­top appli­ca­tions like Out­look, in the case of Tagloc­ity), tag clouds as a type of visu­al­iza­tion have strong prece­dents in other much more mature user expe­ri­ence con­texts, such as the dis­play of mul­ti­ple dimen­sions of infor­ma­tion within geo­graphic or geospa­tial frames of ref­er­ence. Instances of strong cor­re­spon­dence of prob­lem solv­ing approach in both mature and emerg­ing con­texts could indi­cate sim­ple appli­ca­tion of par­al­lel fram­ing (from the mature con­text to the emerg­ing con­text) as an untested con­di­tional, until the true extent of diver­gence sep­a­rat­ing the two con­texts is under­stood. This is very com­mon new media.
Instead, in the case of tag clouds, I think it points at sta­ble needs dri­ving struc­turally sim­i­lar solu­tions to the basic prob­lem of how to visu­ally com­mu­ni­cate impor­tant rela­tion­ships and addi­tional dimen­sions of mean­ing under the lim­i­ta­tions of inher­ent flat­ness. The par­al­lels between car­tograms and tag clouds place the appear­ance of the tag cloud within the larger his­tory of con­tin­u­ing explo­ration of new ways of visu­al­iz­ing infor­ma­tion. In this view, tag clouds are a recent man­i­fes­ta­tion of the sta­ble need to cre­ate strong and effec­tive visual ways of con­vey­ing more than mem­ber­ship in a one-dimensional set (the list), or loca­tion and extent within a two-dimensional coör­di­nate sys­tem (the map).