The city of Cambridge, Massachusetts, on the opposite side of the St Charles River from Boston, Massachusetts, USA, is home to over 107,000 people, some prestigious universities such as Harvard and the Massachusetts Institute of Technology, and numerous cultural and physical amenities. The city is exemplary with regards to how it serves spatial data to the GIS community and to the general public. The city’s GIS portal includes a map gallery of traffic, history, watersheds, community development, elections, wireless access, and other themes that are viewable online, downloadable, and many of which are viewable on a mobile device. One unique and interesting mobile map is the “street trees walking app” that allows a person to identify the type of tree species that are nearby as they walk through the streets of Cambridge. The city’s GIS portal includes numerous interactive maps in their CityViewer utility, including a historical viewer dating back to 1947 with imagery and 1865 with maps. GIS data downloads are one of the richest data sets I have seen from any local government, with over 60 layers on infrastructure, public safety, hydrography, topography, health, demographics, and much more.
One of the unique features of the city’s GIS portal is the use of a story map. The story map was created because, in the words of its creators, “The city has all of these great programs and offerings but they aren’t necessarily advertised in the most efficient manner, and the information isn’t always easily accessible.” Besides showing the public where the city services are located, a side benefit for the GIS community is that the story map itself is a thorough and compelling tutorial of how to build your own story map.
Last but not least, the data dictionary for the City of Cambridge GIS is extremely thorough and easy to use, providing shapefiles and file geodatabases. The dictionary contains information on how and why a GIS layer was created, the city’s procedure for maintaining each layer, departments that contribute to the development of each layer, history, and the intended use of the data. The metadata even includes what some dictionaries leave out–a thorough description of the attributes and how the attributes are defined.
In our book, we discuss the costs and benefits of local governments serving their spatial data to the GIS community and to the public. The City of Cambridge has gone to great effort to make their data interesting, relevant, and easy to find and use to a broad spectrum of data users.
We’ve written a number of posts over the last couple of years on crowd sourced data collection initiatives, all of which have been land-based or involved aerial data (for example, UAV Imagery). The TeamSurv project takes crowd sourced data collection out to sea, enlisting the help of mariners to produce better maps and charts of coastal waters, where the amount of detailed survey data in many countries is low. Project participants will either receive a data logger to use with their existing equipment or be able to load data directly from their own navigation systems.
The data collected from a variety of volunteer vessels include bathymetry, surface currents, sea surface temperature and wind data. Once processed the marine GIS data sets are to be made available to any organisation or authority with an interest in hydrographic data (chart publishers, oceanographers and so on). The charts are available to download from the TeamSurv web site in shapefile format, and the site promises that other formats will be supported soon.
Unfortunately the data are not being made available in the public domain. The conditions of use include the charts are for personal use only and they may not be distributed or reproduced for commercial or non-commercial purposes without written consent. Although this seems contrary to the ethos of crowd sourcing, given the amount of post-collection cleaning and correction the data are subject to, it is perhaps understandable that some restrictions on their use should be imposed. Is it better to have unrestricted access to a lot of data of variable quality, or are some restrictions a price worth paying if the quality of the data can be guaranteed?
Questions such as “How can I obtain geospatial data?” and “How do I know if that data is any good?” are central themes in this blog. One data source that merits attention is the Esri Living Atlas of the World. More than an expanding source of spatial data, it represents the new paradigm of obtaining and using spatial data.
The Living Atlas of the World is a collection of maps and apps on hundreds of topics focused around people, earth, and life. This includes data (1) created by the Esri ArcGIS Content Team, (2) contributed to the online basemaps through crowdsourced participation from the Community Maps program, and (3) authored by Esri partners. Basemaps include oceans, imagery, streets, terrain, and others, and is a mixture of global sets and regional/local sets, depending on who created it. Imagery includes events, basemaps, multispectral, and temporal. Other categories include demographics, lifestyles, landscape, Earth Observations, Urban Systems, Transportation, Boundaries and Places, Historical Maps, and Story Maps.
Navigating the graphics-rich site is quite easy and the metadata exists in an overview set of paragraphs and in a more detailed form as well. A nice touch is the inclusion of person responsible for the curation for each category as well as a short video from each person. Most of the maps and data sets can be opened in the ArcGIS Online map viewer or in ArcGIS Desktop, and in addition, the individual map layers making up the maps can also be accessed. The chief challenge, like with any large data portal, is to determine the most suitable search terms to use in order to obtain the desired data set. One gets the strong sense of the rapid expansion of this portal recently and that it will continue to rapidly evolve.
The Esri Living Atlas of the World represents a new paradigm of serving data for several key reasons. As we indicated in our book, industry is playing an increasingly important role in serving government and other data through their own methods and portals, of which Esri here is a prime example. Second, this portal allows users to immediately begin interacting with the data using cloud-based mapping services; in this case, within ArcGIS Online, but also, with just a click or two, within ArcGIS Desktop. Third, this atlas is not a standalone web page for data access, but rather, the atlas itself is a fundamental part of the ArcGIS platform. If one wanted to save some of the layers in standard vector and raster data sets, one would need to export them through the ArcGIS Desktop package. But if this type of portal is any indication, the need for saving data in a standard format may be quickly becoming “old school.” This may be the case if instead of exporting and importing data, one can use an online atlas and begin using the data for analysis right away.
The Open Data Institute (ODI), founded by Sir Tim Berners-Lee and Prof. Nigel Shadbolt, has been working collaboratively with many partners around the globe to develop a network of open data ‘Nodes‘. Nodes, which aim to bring individuals and organisations together to collaborate and promote the use open data in business, government and education, are split into three levels:
- Country: Independent NGOs building national centres of excellence, working across public and private sectors, NGOs, educational institutions and other Nodes within a country.
- City or Regional: Deliver projects, and can provide training, research, and development. For example, ODI Dubai, ODI Chicago, and ODI North Carolina, ODI Paris, ODI Trento, ODI Brighton, ODI Manchester, ODI Leeds.
- Communications: Promoting global open data case studies. For example ODI Moscow, ODI Buenos Aires and ODI Gothenburg.
Although not a data portal, the ODI provides a variety of resources for those work with open data, including research into how open data is used, how it is published and how to certify open data. Given the current plethora of data sites and portals, not all of which are well thought out and useful as we have commented before on this blog, this invaluable resource of data trends and issues provides many useful references for those working with the various types of open data, including location based data. For example, a recent blog post from ODI North Carolina discussed how important quality is for open data.
It is always helpful for others who are considering working with open data, or who are in the process of collecting and publishing open data, to benefit from the experiences of others. Given the ease with which data can be published online these days, the next challenges are to provide data that are easy to find, well documented, current, accurate and ultimately ….. useful. As Charlie Ewen (UK Met Office) remarked, ‘Digital isn’t done once you have a website’.
In this blog, we have written about the revolution occurring in the remote sensing world, centered on inexpensive and crowdsourced remote sensing. As described in this TED talk from Planet Labs’ Will Marshall, Planet Labs has launched small satellites of the dimensions 10 x 10 x 30 cm, weighing 4 kg, which can take images at 10 times higher resolution than conventional large satellites. Early in 2014, the International Space Station launched 28 of these small satellites. They plan to launch more than 100 that will image the Earth from a single orbital plane as the planet rotates beneath it. Will refers to this system as a “line scanner for the planet.”
While our book and this blog discuss geotechnologies from a technical point of view, we also highlight the societal implications of these innovations. Planet Labs’ work fits in well with these themes, because they are not only technically innovative, but their goal is to democratize remote sensing data. They are asking: “If you had access to imagery for the whole planet on a daily basis, what would you do with it?” Every point on the planet will be imaged every day with their platform.
And while the partnerships and avenues of dissemination data are still being worked out, this and similar efforts in the remote sensing world will surely impact data availability, crowdsourcing, copyright, privacy, decision-making, and other topics important to science, education, and society, in the months and years ahead.