Entradas de Josema Alonso

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The Milky Way over Valdevaqueros Beach


Valdevaqueros is a wonderful beach in the South of Spain, pretty well know to kite surfers. It has a quite high dune on the East end of the beach. The dune moves quite frequently and it’s not unusual to find important amounts of sand on the road next to the beach and diggers removing it to allow cars to pass.

To prevent the dune from collapsing, fences were put in various places in the middle of it, but the strong winds and the dune moves, make them fall and break very frequently and they are no longer replaced.

Photo Story

After a few years spending the summer holidays in the area, I decided I wanted to try something new and attempt my first serious shot of the Milky Way. I had read and watched several tutorials and felt myself prepared. My landscape lens is not that fast (f4) but the Sony A6300 is quite capable in low light so I was determined to try and not to go beyond 3,200 ISO anyway.

I arrived well before sunset to scout the area for one last time before the shot and find a spot good enough to keep some of the fences on the foreground and the Milky Way as the background showing above them. I set there with my beach chair, my sandwich and some water expecting to enjoy the landscape in silence and having it for myself.

It was less than week before the peak of the perseid meteor shower and I also expected to see some of those, too. And I did. Just a couple but stunning.

What I was not expecting, and was an interesting addition, was that a nearby bar had organized a live rock show and I was entertained for free for about two hours in almost total darkness by the distant Spanish rock music.

I started to shot before sunset. My plan was to get a tack sharp shot of the fences in the blue hour and then the Milky Way over them a couple hours later to later blend them both with the best of each.

I shot some 250 frames at 20-30 seconds every minute over about 5 hours.  The Sony PlayMemories timelapse camera app was useful in this regard as it can automate this process as if it was an intervalometer. I was not that lazy so I was occasionally doing some manual adjustments from time to time with care not to move the camera.

Developing Notes

I’m using Affinity Photo as of late for my most complex photo editing and processing and this was what I used to make the blend.

I started with the foreground blue hour shot. I tried to find the one that was sharp enough, and not too warm so it could be then realistically merged with the Milky Way background shot.

José M. Alonso

I then went through all the Milky Way shots until finding one where the Milky Way would be right above the fence and providing a pleasing composition.

José M. Alonso

I created separate layers and used luminosity masks to make the blend.

All right so far, uh? Nope. Error.

My tripod is too light, there was some wind and I was manipulating the camera at times. Result: the tripod moved between shots and the alignment of the fence in both shots was not working.


I had to spend a significant amount of time aligning both properly. Several hours. It was boring.

Lesson learned. Get a better tripod (I’ve just done it) and don’t mess around when the camera is taking long exposures.

Once that done I had to face an expected problem. The blue hour fence at f8 is much sharper than the Milky Way fence at f4, not to mention is much brighter. I created a mask around the fence mostly manually to then use a little bit of warp on the foreground to fill the gaps between the sharp and not so sharp fences. I hope it worked.

I was not annoyed by the light pollution. In case you wonder, the camera is facing the sea and beyond it, the African continent. The light comes from the city of Tangier, on the other side of the Strait of Gibraltar.

I’m pleased with the end result especially to be my first attempt.

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Upper Yosemite Fall from Swinging Bridge


Yosemite Falls is the highest waterfall in North America. Located in Yosemite National Park in the Sierra Nevada of California, it is a major attraction in the park, especially in late spring when the water flow is at its peak.

The total 2,425 feet (739 m) from the top of the upper fall to the base of the lower fall qualifies Yosemite Falls as the sixth highest waterfall in the world, though with the recent discovery of Gocta Cataracts, it appears on some lists as seventh.

Upper Yosemite Fall: The 1,430-foot (440 m) plunge alone is among the twenty highest waterfalls in the world. Trails from the valley floor and down from other park areas outside the valley lead to both the top and base of Upper Yosemite Fall. The upper fall is formed by the swift waters of Yosemite Creek, which, after meandering through Eagle Creek Meadow, hurl themselves over the edge of a hanging valley in a spectacular and deafening show of force.


Photo Story

As most of my landscape photo trips, I took advantage of a business trip to extend my stay and get to take some pictures. I traveled to San Jose in California where I rented a car and got to Yosemite National Park after a circa 4-hour drive. I spent only 3 days there, mainly visiting Yosemite Valley, staying at one of the hotels right outside the park’s entrance, only a 30-min drive from the center of the valley itself.

I came pretty prepared. Having seen Ansel Adam’s pictures and favorite locations many times, I got ahold of a key resource: Michael Frye’s «The Photographer’s Guide to Yosemite.» If you’re into photography and are going to Yosemite for the first time (or even if you’ve been there already, I’d say) you should get it. Maps, photo locations, tips, all is there, very well organized. Saved me lots of time, allowing me to be very effective and to make the most of my short stay.

It was May, so it was packed with tourists and the falls were at their best. In order to extend my days and get advantage of the best light, I decided not to sleep much, getting up at about 4am or earlier.

The morning I got the shot I left the hotel at about 4:30am and went straight to Cathedral Beach to get some shots of El Capitan hit by sunlight at its top. I then went to Swinging Bridge, where you can get the beautiful and quiet view of the Yosemite Falls reflected in the Merced river you can see here. It was really calm and the only other person I found at the location at such time (06:58am according to the EXIF data) was another photographer trying to get the shot, too.

Developing Notes

It was hard to control the flare on the right hand side and I did my best to do so. I’m reasonably happy with how it turned out in this shot.

Although I bracketed as usual, no combination of the bracketed shows made me happy, so I only used one exposure on Lightroom. I applied the lens profile, opened up some shadows, decreased the highlights and increased clarity an vibrance. I also removed some spots from the river (leaves) to get a cleaner reflection effect.

Lake Ercina (Asturias, Spain)


The Lakes of Covadonga (el. 1134 m.) are of two glacial lakes located on the region of Asturias, Spain. These lakes, often also called Lakes of Enol or simply Los Lagos, are Lake Enol and Lake Ercina located in the Picos de Europa range and they are the original center of the Picos de Europa National Park, created in 1918.
The road ascending from Covadonga to the lakes is a popular climb in professional road bicycle racing, having been used by Vuelta a España many times in the last 25 years.

Photo Story

Getting to the Lakes of Covadonga is pretty easy. You can get there directly by car. The last few kilometers from Covadonga itself are rather narrow and twisty but not complicated in any case. Just take it easy and even stop from time to time at one of the (few) viewpoints such as Mirador de la Reina from where you can see a beautiful sea of clouds and eventually the sea.

I planned to be at the lakes some two hours before sunset. There are parking lots nearby and getting to the lakeshore itself is just a matter of a few minutes. The lakes themselves are connected by a short trail that allows you to enjoy beautiful views of any or both.

Laker Ercina from trails between both lakes

BTS: Lake Ercina from the trail between both lakes

I took quite a few shots from different locations but my goals was to get one with a nice reflection. I approached the lake from different angles. Composition was a bit difficult as there is a mountain on the right but none to fill and compensate on the left so I played a bit with the tripod location until I got what you see here, leaving the tripod as close and low as possible to the water as I could, right when the best moments of the sunset were starting.

Developing Notes

This is mainly a combination of three exposures made with a Haida ND3.0 filter on to smooth the water and clouds.
On one hand, we have three bracketed shots at -2, 0, +2. These were merged using HDR Efex Pro 2 and keeping the effects pretty subtle. Despite that, some of the colors looked a bit overdone in the end but my main goal was to recover the texture from the rocks everywhere.

The 0 exposure was developed in Lightroom 5.7 mainly opening shadows and recovering some highlights. The skies in the first case were not usable as they had too many artifacts due to ghosting and the combination of such long exposures. The sky of this one was sort of ok, but still way too blurry for my taste.

HDR sky

HDR sky

Long exposure sky

Long exposure sky

I also took an additional exposure without the ND filter for the sky.

The three resulting images of every aforementioned step were imported into layers in Pixelmator 3.3.1. I merged the first two ones by masking the HDR version a bit here and there to recover more natural colors on the LR version and finally merged this with the sky of the third image.

Counting Datasets Is Bad

I’ve just learned about next.data.gov, and at first glance it looks much more usable than the well known data.gov version. This CKAN-based deployment made me wonder about the future of the OGPL, but I digress…

When getting to the data catalog, I was greeted with this message at the top of the page:

where I found out that data.gov is now hosting 75,712 datasets. I followed the link to the site’s homepage and found this:

So apparently, the figure was not the right one as the number of datasets seems to be 152,977. So I followed the link to the catalog and got this:

Hmmm… I’m confused.

Since the new webiste announcement was part of the fourth aninversary announcements, I reminded other announcements in previous anniversaries. So, for example, as part of the third anniversary announcement, we could read: «Growing from 47 datasets in 2009 to nearly 450,000 datasets today…»

I’m even more confused. The progress and growth of data.gov has been significant. The number of agencies publishing datasets (174 at the time of writing) has grown over the last four years and in the best case scenario what I’m seeing is roughly about one third of datasets on the catalog compared to one year ago? I haven’t found the time to look in depth just yet but I’m pretty sure that’s not the case but more a matter of a usability issue on one hand and different ways of counting datasets over time on the other.

This shows something I mentioned quite a few times before and that gives title to this blog post: counting datasets is bad. And, in fact, is quite meaningless.

I understand that data catalogs need to show a total number somewhere but the issue here is the interpretations that might be derived from it. I heard people claiming that catalog X is better than catalog Y because they are publishing so many more datasets and, frankly, this is a totally questionable claim. In fact, we’re yet to determine what makes an open data catalog good and why catalog X can be considered better than catalog Y.

The bottom line to me is: the number of datasets is just a simple metric that tells very little about the usefulness of an open data catalog.

We need more research to understand these issues and the impact of open data in general, even to understand whether or not an open data central point of access (a data.gov.* website) is the best way to achieve the promised benefits of open data.

Struggling with Open? Data

A colleague of mine pointed me today at an interest resource for mobile-related statistics. The Mobile and Development Intelligence website hosts several datasets on the developing world mobile industry and beyond. Ken Bank’s blog mentions this has been done by the GSMA team, in partnership with ThoughtWorks and PwC, and investor the Omidyar Network.
The about page states that «MDI is an Open Data portal for the developing world mobile industry. We believe that open access to high quality data…»

So far, so good.

I then tried a sneak peek at the data and this is what I found, a sign in/register page:

MDI login page

No, I’m sorry, but whatever you have behind this it’s not open data.

The terms and conditions are not much open either. The licence section states that «GSMA grants You a non-exclusive, non-transferable, non-assignable licence to use and/or to access the Web Site and Data therein.» So what if I want to re-publish the data, e.g. I use some of that data with data from other sources, mash it up, and want to re-publish as open data the end result? Houston, I’ve a problem!
The section on «restrictions and permissions» also worths a read.

Honestly, it’s disappointing we are still seeing this things in 2012, especially coming from such a smart set of partners. I hope this will fixed rather sooner than later.

Note: I then decided to register and also to investigate further, register and, yes, I could doownload the data in CSV format.

A more generalized issue

One I got to the data, I realized that some of it was not from MDI itself but coming from well known sources wuch as the World Bank, IMF and others, according to the sources listed there. In fact, some of the datasets looked familiar, so I decided to compare the data shown at the MDI with (supposedly) the same data as offered by some of those sources (where I can really get it as open data).

Let’s take as an example the rural population dataset, people living in rural areas as defined by national statistical offices:

MDI Rural Population

MDI Rural Population

WB Rural Population

WB Rural Population

The first screenshot above shows the MDI data while the second shows the WB data. Can you spot discrepancies? It’s quite easy to do so. Not big differences but they are there.

MDI list as data sources: World Bank World Developmen Indicators & GDF, while WB lists the World Development Indicators. If I track back these I start to find more sources from UN, etc.

What’s the issue here? On one hand, there’s no direct reference to the data source (ideally a URI) where I can check whether the data presented to me is accurate or not according to the source. On the other, it doesn’t look like raw data to me, more like a combination of sources in a way I cannot really know about. As another example, the Bank’s total population dataset lists the following data sources: (1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database.
Again, no direct links to sources but general pointers at organizations and no mention on how the data has been mixed.

I don’t want to go into much detail in this post about these issues but I wanted to note that in these days where transparency and accountability discussions are all over the place, when I’m hearing concerns about data manipulation every other day, it wouldn’t hurt to seriously think about these and sort them out the soonest.