Month: May 2014

Uneven Geographies of OpenStreetMap

OpenStreetMap_Satellite

Description

This series of maps shows the location of edited content in the world’s largest collaborative mapping project: OpenStreetMap.

Data

The maps use OpenStreetMap data downloaded from GeoFabrik.de on December 12th, 2013. Each sub-region extract has been parsed and for each node (i.e., elements used in OpenStreetMap to represent any point feature), the coordinates, version, and last update values have been selected.

The first map was created by counting the number of nodes for each cell in a grid of 0.1 degrees of latitude per 0.1 degrees of longitude. The second map instead focuses on edits by summing the version numbers of all nodes in a cell (as this number is increased by one each time a node is modified), resulting in a count of all edits for the whole history of OpenStreetMap. The third map focuses on the age of content, and so records the latest update made to a node for each cell of the grid.

Findings

The first map offers a revealing picture of the presence of thick layers of content that annotate a few parts of the world, and a relative absence of content over much of the rest of the planet. The glowing centres of content in parts of North America, Europe, Oceania, and Japan, in many ways, parallels the visual intensity of lights in NASA’s Earth City Lights series.

The United States account for the largest total amount of content, collecting 21% of all nodes present in OpenStreetmap (OSM), followed by France, Canada, Germany and Russia, all counting more than 100 million nodes. These five countries alone collect 58% of the content, and high-income OEDC countries sum up to about 80% of OSM.

The Netherlands enjoy the highest density of content, with an average of over 1000 nodes per square kilometre, followed by Belgium with over 700 nodes per square kilometre, and Germany, the Czech Republic, Switzerland, and France, with about 400 nodes per square kilometre.

In contrast to the brightness of the Europe, the southern hemisphere is barely visible, as the amount of content available on OSM about that part of the world is far lower than in the northern hemisphere, with Africa and Latin America represented by less than 5% of the content. California alone accounts for almost as much content as the entirety of Africa.

Turkey and the western part of the Middle East are visible, but already fading into a less intense color. The emerging powers of Brazil, India, and China appear to be suffering from wide-spread content “blackout”, where only the largest urban centres are visible. Brazil accounts for fewer nodes than Switzerland, and China for even fewer. The same applies to most of the remaining parts of Africa, Asia, and Latin America. One of the oldest urbanized areas of the world, an amazing strip of lights that follows the course of the Nile, is barely visible. In fact, Egypt accounts for as many nodes as Iceland, despite being 10 times as big and accounting for 250 times the population.

Interestingly, content in parts of North Korea lights up the map: an unusual situation for a country not renowned for even appearing in most indices of online participation. This is most likely thanks to work done in 2011 by the OSM developers community. We see a similar situation in Newfoundland and Labrador: with large swaths of sparsely populated land characterised by relatively dense amounts of content. The Canadian case is likely a result of a detailed physical geography dataset that was bulk-uploaded to OpenStreetMap.

Several studies have been conducted on the quality of OSM’s coverage in these areas (e.g., see the paper by Haklay et al, 2010) where high-quality data from government agencies are also available for comparison. However, it has to be noted that these are the same countries where Open Data policies have spread, allowing lots of data to be uploaded to OSM. In fact, the visible distribution of content is not too different from the map of the GeoNames gazetteer project we published some months ago.

The second map below illustrates the number of edits made to OpenStreetMap. Unsurprisingly, the most content-dense areas are also the most heavily edited, because each new node included means one more edit made within the related area. However, statistical analysis suggests that the United States and Germany account for far more edits than would be expected given the related content in OSM, whereas content from Italy and Netherlands is far less edited than expected. In most parts of the rest of the world the number of edits is simply related to the number of objects in a given area.

EditingTheMap

The third and last map presents an illustration of the most and least recently updated areas in OSM, similarly to a map included in the recent Mapbox’s 2013 OpenStreetMap Data Report.

It is not surprising that most areas in Europe have seen at least one edit in the week before the data were collected. Similarly, it is evident how the most remote regions of the world have not been updated for years, from Siberia to the Australian Outback, from central Africa to the Amazon basin and northern Canada.

While most of the map shows a random mix of data, due to the volunteer-based nature of the projects, there are some evident areas of plain colour, which might indicate bulk uploading of new data and datasets from government agencies or companies. An examples can be found in Iraq, where most of the country has been updated between September and November 2013; in Australia, where large areas in South Australia have been recently updated, and the updates clearly follow the state borders with New South Wales and Victoria states; and in Estonia, which has also received recent edits for most of its territory.

TheAgingMap

OSM will turn 10 years old in a few months, and combining the findings obtained from these three maps, it is evident how it is a very good geographical representation of the most developed countries, and their urban environment. OSM also provide large amount of information about non-rural areas, although these are not as up-to-date and detailed as urban areas.

The quantity and the quality of the data make OSM one of the most powerful and exciting open-source projects that the Internet has facilitated in recent years, along with Linux and Wikipedia. Nonetheless, there is still a lot of work to do, and the development of the project in its second decade will probably depend on it attracting new volunteers among the new Internet users in Africa, Asia, Latin America, and the Middle East. Finally, OSM will be influenced by the relationships with those many companies which are currently based their mapping services on it, as well as the future spread of open data policies.

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A global division of microwork

ODesk-A_global_division_of_microwork-final-01

Description 

This graphic illustrates the global division of microwork undertaken on the ODesk platform and reveals some of its locally divergent practices.

Data

Microwork refers to a series of relatively small tasks that are carried out by a distributed workforce over the Internet. Practices of coordinated microwork therefore allows for relatively large projects to be carried out quickly by workforces from around the world. ODesk is one of the largest job marketplaces for microworkers. This graphic uses openly available data from ODesk, describing the hourly working practices of microworkers (i.e., the number of active workers per each hour of the week) in each country across the globe.

In the first visualisation, each dot represents the average number of workers active in each country for every hour of the week. For countries that span more than one time zone, we use the local time in the capital city.

The second visualisation uses the same data, but makes two changes. First, dots are aligned according to local time, rather than Coordinated Universal Time (UTC). Second, dots are aligned according to UTC  and the size of each dot is normalized by the Internet population in each country. These changes offer a sense of how prevalent online microwork is in each country, and allows working hours between places to be directly compared.

The representations do not account for the use of daylight saving time.

Findings

The first image shows that a large portion of the world’s microwork carried out through ODesk is carried out in Asia: particular in the Philippines, Bangladesh, India, and Pakistan. At noon (local time) on an average Tuesday, there are almost 35,000 active workers on the platform, roughly one third of whom are located in India, about one quarter in the Philippines, and about one tenth in the United States. Russia and the Ukraine also each provide over five percent of the total. Despite the fact that ODesk is used in 58 countries that cover almost every time zone, 85% of the digitally mediated workers are located in the seven countries mentioned above. In other words, despite the potential for almost anyone with an Internet connection to become a microworker, we can see that microwork practices have very clustered geographies.

One interesting facet of these data is the significant different between working patterns in the Philippines and most other countries. In most countries, it is easy to distinguish the difference between day and night by the sharp drop-off in work that happens at the end of the working day. However when looking at the Philippines we only see a relatively minor change in working practices between the day and night.

In many countries we also see a stark difference between weekdays and weekends. However, the Philippines again exhibit a relatively consistent temporal pattern with fewer people than elsewhere avoiding work on weekends. By 3am (Philippines time) on an average Sunday morning, the Philippines provide almost half of the active workers in ODesk.

Some of these patterns can be traced to the large US demand for microwork. Filipino microworkers are mostly employed to complete tasks related to data entry, writing, and a variety of personal assistance work(see ODesk Philippines Country Dashboard). We see an increase in the number of active Filipino workers when it is morning in the US (9am Eastern Standard Time: which is 10pm in the Philippines). Bangladesh also exhibits a similar pattern to the Philippines. Bangladeshi microworkers are also largely employed for data entry, with the most common type of task performed in the country relating to search engine optimization (see ODesk Bangladesh Country Dashboard).This contrasts to the situation in India, where most microworkers are employed for tasks related to Web programming and design (see ODesk India Country Dashboard). In India, we see the number of active workers decline in the US morning (9am Eastern Standard Time: which is 6.30pm Indian time).

The second image, weights the number of active microworkers from each country against that country’s Internet population. This gives us further insights into some of the country-specific differences in microwork practices. For instance, we can see that not only does ODesk have a large and around-the-clock workforce in the Philippines, but that the platform is also relatively popular in that country. On an average Tuesday at noon local time, ODesk employs 0.025% of the entire Filipino Internet population. This is almost ten times the global average. By way of comparison, the platform employs only 0.001% of the US Internet population.

Online microwork also appears to be relatively popular in Armenia and Moldova (in both countries over 0.01% of the Internet population are active on an average Tuesday at lunch time), mostly employing micoworkers in the fields of Web programming and design. In South America, Uruguay and Bolivia also demonstrate relatively high rates of microwork activity; Bolivia is particularly interesting because it is the only country that exhibits a visible decline in the number of active workers in the middle of the working day.

These data offer a fascinating insight into new practices of work in our global knowledge economy. The ability to carve up large projects into small digital tasks that can be performed by a globally distributed labour force has meant that global demands for, and supply of, digital tasks can be easily matched. But it remains to be seen whether these new work practices are a useful employment opportunity for many of the two and a half billion connected people in the world, or whether they represent a new type of digital sweatshop in which the world’s poor are enrolled, as expendable and unorganized workers, into exploitative digital divisions of labour.

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