Gothos

The GDAL / OGR tools are an open source, cross platform, command-line toolkit that can be used for viewing GIS metadata, performing attribute queries, and converting file formats, among other things. It can also be used for transforming coordinate systems and projections for GIS files. I’ll demonstrate in this brief tutorial how to accomplish this using the OGR tools, which are for vector based GIS. The raster based GDAL tools work in a similar fashion.

Viewing basic coordinate system / projection info:

ogrinfo -al -so world_wgs.shp

Where ogrinfo is the name of the tool, -al is a switch to get detailed info about the layer, -so is a switch to display summary info, and world_wgs.ship is the name of our file. Run that command and we’ll get something that looks like this, with info about the features, coordinate system, and attribute fields of our shapefile:

INFO: Open of `world_wgs.shp’
using driver `ESRI Shapefile’ successful.

Layer name: world_wgs
Geometry: Polygon
Feature Count: 243
Extent: (-179.808664, -89.677397) – (179.808664, 83.435942)
Layer SRS WKT:
GEOGCS["GCS_WGS_1984",
DATUM["WGS_1984",
SPHEROID["WGS_1984",6378137,298.257223563]],
PRIMEM["Greenwich",0],
UNIT["Degree",0.017453292519943295]]
CNTRY_NAME: String (254.0)
FIPS_CNT_1: String (254.0)
ISO_2DIGIT: String (254.0)
ISO_3DIGIT: String (254.0)
STATUS: String (254.0)
COLORMAP: Real (18.6)
CONTINENT: String (254.0)
UN_CONTINE: String (254.0)
REGION: String (254.0)
UN_REGION: String (254.0)

Convert coordinate systems supported by EPSG

GDAL / OGR and most of the open source GIS software supports projections and coordinate systems that are part of the EPSG library. If you want to do a conversion between two coordinate systems and they are both supported by EPSG, you just have to reference the EPSG code that’s used to identity the system that you want to project to. You can look up codes using spatialreference.org.

Let’s say we want to convert our shapefile that’s in WGS 84 (common lat and long) to NAD 83 (used frequently in North America):

ogr2ogr -t_srs EPSG:4269 world_new.shp world_wgs.shp

Where ogr2ogr is the name of the tool, -t_srs is the command for transforming from one coordinate system to the other, EPSG:4269 is the code that identifies the coordinate system we want the new file to have – NAD83, world_new.shp is the name of the output file that will have the new projection that we want, and world_wgs.shp is our input file. If you run the command and get no error message, you’re in good shape. Just run the ogrinfo command on the new file to verify that it’s been re-projected.

Convert coordinate system not supported by EPSG

The EPSG library is extensive, but doesn’t contain everything, particularly some global and continental map projections. GDAL / OGR can still do the job, but you’ll have to provide the tool with the proper frame of reference since the EPSG library doesn’t have the info. Let’s say we want to project our WGS file to the Robinson Projection, which is not part of EPSG.

First, go back to spatialreference.org and search for Robinson. Its ID code is ESRI 54030 – not part of the EPSG library. Click on the link for the projection to open its window. You’ll be able to look at the projection data in a number of standard file formats. Select OGC_WKT from the list, and it will open the text in a new window, showing you the parameters of that projection. In your browser, go up to file, save as, and save the file as robinson_ogcwkt.txt in the same directory as the shapefile you want to reproject.

Now that you have the projection info stored in the text file, run the following command to make the conversion:

ogr2ogr -t_srs robisnon_ogcwkt.txt world_rob.shp world_wgs.shp

It’s the same command as our previous one, except that you’re referencing the text file with your data instead of an EPSG code.

Define an undefined coordinate system

If you run the ogrinfo command and your coordinate system is undefined, you should define it before doing anything else, and you must define an undefined projection before converting to another projection. Look at the metadata that came with you file or go back to the source to figure out what it is. For example the US Census Bureau Generalized Cartographic Boundary Files for 2000 are in NAD83 according to their metadata, but the files lack a projection definition.

To define one, use the following command:

ogr2ogr -a_srs EPSG:4269 states_nad83.shp states_unknown.shp

The only difference here is the -a_srs command is used to assign a coordinate system to a file – the rest of the parameters are the same. If you’re defining a non-EPSG projection, use the same method from the previous example – download a definition file from spatialreference.org and use the file name in place of the EPSG code.

More help and where to download:

UC Santa Barbara NCEAS and the UC Davis Soil Lab both have short tutorials and sample commands of GDAL / OGR.

If you want to thumb through the world’s map projections, the folks at radicalcartography have a nice projection reference page with visuals and brief descriptions.

Visit the GDAL / OGR page for downloading, or if you’re a Windows or Mac user, you can download QGIS and GDAL / OGR together from the QGIS download page. Linux users can get GDAL / OGR via your package handler – depending on your distro, you may have it already.

A little while ago I posted a text file with geographic centroids (centers) for each of the world’s countries. The reason why I put this together was that I wanted to test the data defined labeling features in QGIS. While automatic labeling in QGIS isn’t so hot (overlapping labels, multiple lables for each polygon), there are some powerful features for storing and referencing columns for annotation within the attribute table of shapefiles. One of the neat features is the ability to place labels based on coordinates stored in the attribute table.

The first step was to take the centroids file and join in to a shapefile of the worlds countries based on a common ID field, in this case FIPS country codes. QGIS doesn’t support table joins directly, but you can accomplish this with a good plugin called fTools, which includes a lot of additional and useful features. The instructions for getting fTools up and running are available on the fTools website; the installation doesn’t require you to download any files, you just handle everything through the QGIS plugin manager (if you have trouble seeing the plugin manager or getting fTools to appear, check to make sure that you have python installed on your machine). Once fTools is up and running, you’ll see a Tools dropdown menu next to your other menus – drop it down, select data management tools and join attribute tables. You’ll get a dialog box asking which shapefile and field you want to join and which shapefile or table you want to join to it. The plugin only supports joins from other shapefiles and dbf tables, so you have to save the save the country centroids text file as a dbf before you do the join (you can do this in Calc or a pre-2007 version of Excel). These aren’t dynamic joins; fTools will create a new shapefile with the table fields attached.

Once the join is complete, you can add the new shapefile with the new fields, click on the layer, and navigate to the labels tab. Hit the checkbox to turn the labels on, select the field that contains the label in the dropdown box at the top, then select data defined position from the menu below. You’ll see a new series of dropdowns on the right, and you can select your longitude column for the X coordinate and latitude column for the Y coordinate. Hit OK, and voila! You’ll have labels that are centered in the middle of each country.

Of course, the label placement will not be perfect in every case. There will be label overlap in areas with small countries, areas with many countries clustered together, and with countries that have long names. The scale and size of the font will also be a factor, and placing the country name in the center is not always ideal for small island nations. However, you can easily change the label placement by going into an edit mode and changing the coordinates in the attribute table to get optimal placement. You can mouse over the map and use the coordinate information that’s displayed beside the scale in the lower right-hand corner of the window to determine which coordinates are most optimal for a given situation. If you produce several maps at the same area and scale, you can use the same settings over and over again. You can also globally change the placement of all the labels using some of the other label options, such as placing all labels above or to the top-right of the centroid.

Now in order for all of this to work, the coordinates in the country centroid file must be in the same coordinate system as the shapefile. Since the country centroid file uses basic latitude and longitude, I was able to do this with a shapefile that was in the basic WGS 84 geographic coordinate system. If you’re using a different geographic coordinate system or a projected coordinate system, you’ll have to convert the coordinates in the centroid file to match that system. I haven’t delved into this too deeply yet, but there are a number of free tools that you can download that should do this – one of them is called GEOTRANS, and it’s available for free download from the NGA. It can handle batch transformations of coordinate data stored in text files, and supports conversions to several different geographic and projected systems.

QGIS Label Placement With XY Coordinates

I just added a new resource and updated another one on the resources page. I put together a file that contains the centroids (geographic centers) of all of the countries in the world, plus a few territories and dependencies. The centroids are in latitude and longitude coordinates based on WGS 84 in two formats: decimal degrees and degrees / minutes / seconds. It’s a tab delimited text file that you can open or import into any spreadsheet or database program. Each record is uniquely identified by a FIPS 10 code.

I downloaded most of the data from the NGA’s GeoNames Server (GNS). I blogged about the GNS awhile back, pointing out that you could query this gazetteer for individual places or you could download files that have all the features for each country in the world. While it took some time to figure out, you can actually take a middle road and query the database for specific categories of features that you can download. I used the text-based search and the links on the left side of the screen actually open different input boxes that you can use to query or exclude data. I managed to query top-level administrative units (countries) and to exclude most variant country names. After I downloaded the file, I still had to go in and do some clean-up, and I had to go back and get countries I missed by hand – these were mostly dependencies and territories that were excluded based on the search I did (Greenland, French Guiana, Netherlands Antilles, and a number of others).

Then I realized that the GNS excludes the United States and all of its territories. So, I went over to the USGS Geographic Names Information Service (GNIS) and grabbed the data for the US territories. The GNIS is simpler to navigate and you can download records pretty easily. They didn’t have a record for the United States as a whole, so I had to go over to the Census Bureau to get coordinates for the US centroid.

I brought all of these records into one file and placed it on the resources page for download, along with some metadata to describe it. Why would you want to use this stuff? You can use if for basic distance calculations, or as a annotated label field for label placement in GIS. More about that in my next post.

I also updated the country code cross-reference file that I took from the CIA World Factbook. You can use this as a bridge table to relate tables that use different identifiers. So if you wanted to join the fips-based centroid file to an iso-based shapefile of countries, you can join the centroids to the bridge first based on fips, and then that new table to the shapefile based on iso.

This is kind of a follow-up to my last post – the Social Explorer, a great interactive mapping site that allows you to map US Census data, has added the 2005-2007 American Community Survey data to their site at the PUMA level. This is the smallest geographic area that is available for recent data, until we get to the 2010 Census and 2010 ACS. At this point you can look at total population, race, and Hispanic ethnicity. It looks like you can make maps, but you can’t export the data unless you subscribe to the full version.

The Social Explorer allows you to map a wide selection of decennial census data all the way back to the 1790 census (they have a partnership with NHGIS, which provides historical data and boundary files for free download with registration). Tract-level data is available back to 1940. While you can map the data, and you can generate slideshows and download static maps as image files, you can only generate reports for the 2000 census. In order to get full access for report generation and other features, you’ll have to subscribe (or find access to a library that does).

Social Explorer also works with ARDA (Association of Religious Data Archives) to create maps of county-level religious affiliation (since the US Census does not collect this data by law). Of all the interactive mapping sites I’ve seen, the Social Explorer is one of the slickest and easiest to use.

I’ve been on an open source GIS tear this month, so in this post I’ll wrap up some odds and ends:

• There is a project called Sextante, which is essentially an open source ArcToolbox for gvSIG. It adds a lot of geoprocessing and analysis functions and is pretty easy to install. There are 200 + tools in the box, but for some reason not all of them are active. I’m not sure why this is the case, but haven’t poked around much to find out.

• There are also a number of extra plugins for QGIS that are available through the QGIS wiki under PluginRepository; they include plugins that add more symbolization and that make table joins possible. Haven’t had a chance to try this yet either, but it sounds like these extras could make QGIS a lot more viable as a thematic mapping option.

• I found out about the QGIS plugins from this article, which offers a good overview of QGIS. The article also discusses one of the other shortcomings of open source GIS – the lack of a support for a simple, desktop geodatabase similar to the Microsoft Access personal geodatabases. PostGIS is certainly powerful and there has been a lot written about it, but a server based geodatabase is not always the best solution, particularly for small, stand-alone projects. There is a cool project called Spatiallite, where someone has created geographically enabled SQLite databases (which are small, stand alone dbs). You can export shapefiles to them, or simply view and edit the attributes in a shapefile via a virtual connection. Based on what I’ve looked at thus far, you can access SQlite databases directly in GRASS and when using GRASS datasets via QGIS, but I haven’t been able to connect to a SQlite db with the other software I’ve looked at – it’s just not supported yet.

• In researching open source GIS, I’ve looked at a book specifically on GRASS, Open Source GIS: A Grass Approach, as well as two books on web mapping (GIS for Web Developers: Adding ‘Where’ to Your Web Applications and Web Mapping Illustrated: Using Open Source GIS Toolkits)which cover GDAL and OGR, QGIS, GIS servers, PostGIS and PostgreSQL, and a few other tools. There is a book that’s recently been published that focusses specifically on Open Source Desktop GIS – Desktop GIS: Mapping the Planet with Open Source Tools. I pre-ordered a copy on Amazon that was supposed to ship in Mid September, but is now being delayed until late October. Based on the table of contents it looks pretty thorough and covers many of the choices I listed in my previous post, and I’m looking forward to its arrival.

Last week I shared my adventures evaluating open source software. Why bother looking at alternatives to ArcGIS? There are significant barriers of entry to ArcGIS. Whenever I give an introductory GIS presentation to anyone, I inevitably have to answer the question of “How can I get access to this software?” Inevitably, the answer is you have to spend a lot of money, or if your institution already has a subscription, you need to go through a lengthy process to get access.

• Price. A single, stand-alone copy of ArcView costs $1500. Not only is that prohibitively expensive for me, it’s impossible for students. Which means that students who are taking a GIS class have to use the software in a computer lab on campus to complete assignments. This is not always convenient for many students, and is particularly problematic where I work since we are primarily a commuter campus.

• License limitations. If you’re running Arc through a central license server, PCs have to be connected to the server through a hardwired connection – no wireless. Our library has a laptop checkout program for students which would give students an alternative to using a computer lab. But not being able to install the software on a laptop eliminates this possibility. It also makes it a pain for me to give presentations, as I always have to make sure that the room I’ll be presenting in has the software. My short term solution is to use an eval copy on a laptop. You can purchases USB keys that have the license info on them, but if you work in a large, complex academic or government setting, getting one can be a challenge. And every year we have to go through the process of getting the license renewed.

• Installation and Bugs. As Arc users know, installation can be time consuming, particularly since you can’t have two versions of Arc installed concurrently – you have to uninstall one before installing the new one. And how many service packs have been issued for version 9.2? Six. IT people love it when they have to install fixes in a dozen labs / classrooms in the middle of a semester, particularly when they have to do it 5 or 6 times a year. In reality, we skip several service packs and live with the bugs.

• Forced Obsolescence. This is particularly aggravating. Every year or two, we all have to go through the ritual of making an upgrade, which involves time consuming un-installation and installation. And you need to make sure that different branches of your organization that use GIS are on the same page, otherwise you’ll run into incompatibility issues (like when mxd files created in version  9.2 don’t work in 9.1).

• Cross platform. I run a linux box at home and occasionally would like to take my work with me. There are a number of students and faculty members at my school who are ardent Mac users. But ArcGIS runs only on Windows.

The open source alternatives are free, easy to install (usually), can be installed anywhere without restrictions, the software doesn’t expire, and upgrades are a rather simple affair. The obvious downside is that none of them have the power, scope, or usability that ArcGIS has. At least, not yet.

I’ve been exploring the open source GIS alternatives, and have been pretty overwhelmed by the number of choices. For an overview of what’s out there, you can check out The State of Open Source GIS (a large pdf) from Refractions Research, and a series of comparison tables assembled by a geography prof at the Univ of Calgary. You can also search the web for “Open Source GIS”, and you’ll find a number of blogs, forums, lists, and sites that cover it in some detail.

There are a lot of alternatives, and many of them are geared to a particular purpose: raster vs vector, viewer vs map making vs analysis, etc. I’m looking for something that’s cross-platform that I can use for vector-based thematic mapping, and something that I can easily introduce and teach to novices. I need software that allows me to: work with common formats like shapefiles, transform projections, add data tables and join them to shapefiles, symbolize data with a good selection of color schemes, classify data with several methods including natural breaks, add labels, and produce maps as pdfs, images, or in print. Preferably, I want something that has strong map layout capabilities. I don’t want to use a graphic design package for final map creation.

I’ve looked at five options that are all great, but there isn’t one that covers everything I’m looking for :

• GRASS – an established and powerful GIS. Setting up the environment for working with files takes some getting used to (you can’t simply open a window and start adding files), and the native graphic interface is complex. GRASS only works with it’s own native file formats, so you have to import everything into that format first. GRASS was really designed for analysis and modeling (tasks for which it excels), but is not the best choice for basic thematic mapping, or for novices.

• QGIS – one of the strongest attributes of QGIS is that it harnesses the power of GRASS in a more user friendly environment. If you use the GRASS plug-in and work with GRASS datasets, you can do table joins and have access to several classification methods. If you use QGIS on it’s own (working with shapefiles or raster images), you won’t have these capabilities. It seems that projection transformations are limited to a certain subset of projections, and common global thematic map projections like Robisnon or Winkel Tripel are missing (you would have to create them manually). QGIS does have a print layout screen bu color schemes are limited, and labeling isn’t good – it automatically labels every single polygon in a multi-part layer, and the only way to turn it off is via a hack. QGIS is a great viewer (particularly for rasters) and is a good alternative GRASS front end, but probably won’t be your choice for making high-quality thematic maps.

• gvSIG – billed as an alternative to the old ArcView 3.x, gvSIG lives up to this reputation. A map project has separate, defined areas for data views, maps, and data tables. You can do projection transformations and it does support EPSG and ESRI, but the process is a little confusing. The map window has a default projection, but when you add a layer it uses the layer’s projection but keeps the windows projection, and it’s difficult to figure out what projection the layer is in (if this makes any sense!) You can do table joins, and there is a good selection of color schemes for classification and several classification methods. It is the only one that I’ve seen that has natural breaks as an option. It also has the best map layout compared to the other software I’ve looked at and you can export maps out to a number of formats. The biggest weakness is labeling, which is very rudimentary. It doesn’t place labels in the center of polygons, but offsets them slightly (appropriate for points but not polygons), and has no conflict detection. It does allow you to create annotation layers, and improvements are in the works for the next version. Since the software was created in Spain, you’ll occasionally find a menu here or a button there that was missed in translation to English.

• uDIG – the windows and toolbars are not as GIS-like as the other software options, which makes findings things a little tougher. Udig has good projection transformation support, great selection of color schemes for symbolization, and excellent label placement (the best, by far), with conflict detection and different placement options. Like QGIS, the map layout screen is located under the print option. The templates are rudimentary but are easy to use and get the job done. The detractors here are data classification (natural breaks is not a choice) and table joins – there is no option for adding and joining attribute tables to spatial files whatsoever.

• OpenJUMP – has a great interface, particularly for working with attribute tables, good selection of color schemes for symbolization and good label placement features. Table joins are supported for text files (no DBFs). Equal Intervals is the only data classification method available (no natural breaks), and projection transformation is only available via a plug-in. The bigger issue is that there is no print option or map layout. These are available through a plugin as well, but I haven’t tried installing it yet. Plugin installation requires altering or over-writing some of the program files, and I was dubious to try.

There are always work-arounds to fill in the features that are missing. For file and projection transformations, you can always use the GDAL / OGR tools, which I would recommend (although annoyingly I can’t seem to get the projection transformations to Robinson or Winkel to work). The NCEAS at UC Santa Barbara has a nice wiki with examples of commands. Table joins can be accomplished outside the GIS using a database package. You could use a spreadsheet or stats package to figure out break points for data, and change the breaks manually in the GIS. For labels, you can export labels out as annotation, or you can convert polygons to points and use the points layer as a label layer (just make the points invisible but turn the labeling on). Then you can edit that file and move the labels around to get them in the right position. If you make lots of thematic maps for the same area, you can use the same label file over and over again.

This isn’t an exhaustive overview and I haven’t created a consistent procedure for testing all the options. There are a few other elements that I would also want to explore (How good is the support for legends? Can you normalize data or calculate new attribute fields? Can you add a graticule? Change the background color for a view? Convert a table of XY coordinates to a point layer? Is there a geoprocessing tool for generalizing layers?)

If pressed, which option would I choose? I’m inclined to go with gvSIG, which really reminds me of the old ArcView, and would hope that label placement improves with the next version – each of these software packages are constantly improving works in progress. Perhaps it’s best to regard these software options as different tools in one toolbox. If I need to make a thematic map of the world, showing population by country with only a few labels, then I’ll go with gvSIG, where I can easily do table joins, use natural breaks, and have lots of colors at my disposal. If I need to make basic reference maps, say ZIP codes of the NYC metro area, then I’ll go with uDig, as I’ll be able to quickly label them all and still have good color scheme choices. If I need to do geoprocessing or analysis, I’ll also have to evaluate the options – maybe look at plugins, or hunker down and learn GRASS.

In the end, I’m certainly grateful that there are solid, open, and free choices out there and that people are freely giving their time and talent to everyone’s benefit. Why consider these alternatives? I’ll cover that in my next post.

I’ve created a bridge table to relate various country codes: FIPS 10, the three versions of ISO 3166 (two alpha, three alpha, and three numeric), NATO, and the internet country codes. Ok, ok, I didn’t create it, the CIA World Factbook did and has it listed in their appendix, but in HTML. I just copied it and made it database friendly: fixed column headings, removed dashes for nulls, removed trailing and leading spaces, converted numeric codes to text while preserving zeros, and saved it in a tab-delimited text file. You can download it from the Resources page.

If you open it in Excel, Excel annoyingly converts the three digit numeric ISO code back to a number and drops the leading zeros. You can fix this using a trick I illustrated in a previous post, or import it into Calc or Access instead. You’ll be able to designate that field as text during the import process. If you stash the table in a geodatabase, you will be able to relate features and tables that use different codes through this bridge table.

I was also searching for the ISO 3166-2 codes for 1st level subdivisions within countries (like states in the US or provinces in Canada), but had trouble finding anything official as I think they may be copyrighted. I eventually found one source that claims that they received permission to post the codes, so you can take a look there. I also stumbled across a good reference source called Statoids, which gives you background information, lists, and codes for subdivisions on a country by country basis. I’ve added both of these to the Links – Resources page.

I’ve been looking for census data for various countries, and have visited the usual suspects that aggregate this data – the CIA World Factbook and the United Nations Population Information Network. Other supra-national orgs like the IMF and World Bank also create and compile this info. These are fine sources, particularly if your goal is to look at basic data for several (or all) countries. But if you are studying or writing about one country in particular, it may seem odd to cite the UN, and even odder to cite the CIA. It would be better to go right to the source – the chief statistical agency in that particular country. In all likelihood, this agency would also have more in-depth stats than the aggregators.

But – where is the source? Rather than be left to the mercy of google, where you’ll uncover the obvious suspects and lots of commercial sites and joe-schmoes who republished some data from last decade, visit the US Census Bureau’s list of foreign statistical agencies, which will lead you right to the source.

Assuming you can find some pages with some data (census data isn’t public domain in every country and isn’t necessarily online for free, or at all, in which case you may need to go with some of the aggregate sources), the next obstacle will be overcoming the language barrier. Many countries will publish pages in several languages, including English. Some may publish only limited info in English, or no info in English at all. If you don’t read the lingua franca, you can try a translating tool like Babblefish or the Google Language Tool to translate the page for you. The translation may not be perfect, but it should be good enough where you can figure out what you need (although if the language you are translating doesn’t use the Roman alphabet and Arabic numerals – i.e. 1,2,3 etc, you may have some trouble).

The toughest obstacle to overcome may be the organizational barrier. If you are familiar with the US Census Bureau, you’ll know that it’s a large and complex organization with many subdivisions and datasets (decennial census, acs, population estimates, etc). And despite it’s enormity, it doesn’t collect all socio-economic data (religious affiliation) and may not be the best source for all data (current labor force stats). Well – other countries are just as complicated, so be wary!

Another strategy would be to visit Wikipedia – not to cite as a source, but to find what sources they use. You’ll find many country specific articles that cite the CIA Factbook or the UN, but some of the more detailed and well written ones do cite reports written by the statistical agencies for the country in question, often with a link to the page or report. If you have access to some library databases, like Gale Virtual Reference, they will (usually) cite sound references as well. Happy hunting!

Last week, I met Prof John Maciuika , a Baruch CUNY professor who is one of the Academic Directors of the Hypercities project. Created by the UCLA Center for Digital Humanities, this site is essentially like a geographic content management system for cities. Built on the Google Map interface, users can explore city streets and features for a variety of time periods. Historical maps have been scanned in, and current features from Google can be layered on top. For each historical period, you can see photos, video, commentary, and Google KML files for several landmarks – buildings, parks, and districts.

If you register with the site, you can create your own account where you can upload your own content. For profs who want to use this as part of their teaching, you can grant access to portions of your account to groups (a class for instance), where they will be able to view and interact with your content. For example, students may need to explore various architectural projects by visiting them on the map, and then they could upload their assignments (and even photos of their own) to the map where the rest of the group can see them.

Currently, Berlin is the featured city and the one that has the most complete content. There is some content for Los Angeles, and there are plans to add New York, Chicago, Paris, and Beijing. Check it out at http://www.hypercities.com/. It’s still a work in progress, so some of the features may not be active yet.