Russian Sledges

Everything you need to know about Chinese sandwiches. 

swords-n-roses:

Let’s go to the outside world.

Impostor syndrome has been covered extensively in recent years. Its inverse, known as the Dunning-Kruger effect, is at least as pervasive: our innate tendency to confidently claim expertise in topics we know very little about, sometimes to embarrassing (if not tragic) results. Writing for Pacific Standard, David Dunning, who led the first studies of this phenomenon, explores the ways in which our inflated sense of knowledge is a defining attribute of human nature.

The way we traditionally conceive of ignorance—as an absence of knowledge—leads us to think of education as its natural antidote. But education, even when done skillfully, can produce illusory confidence. Here’s a particularly frightful example: Driver’s education courses, particularly those aimed at handling emergency maneuvers, tend to increase, rather than decrease, accident rates. They do so because training people to handle, say, snow and ice leaves them with the lasting impression that they’re permanent experts on the subject. In fact, their skills usually erode rapidly after they leave the course. And so, months or even decades later, they have confidence but little leftover competence when their wheels begin to spin.

In cases like this, the most enlightened approach, as proposed by Swedish researcher Nils Petter Gregersen, may be to avoid teaching such skills at all. Instead of training drivers how to negotiate icy conditions, Gregersen suggests, perhaps classes should just convey their inherent danger—they should scare inexperienced students away from driving in winter conditions in the first place, and leave it at that.

Read the story

Björk talking about her TV

CINCINNATI—Following a traffic stop earlier this month by a University of Cincinnati police officer that ended in the shooting death of an unarmed black motorist, authorities confirmed Thursday that the disturbing video recorded by the officer’s body camera clearly and graphically shows the current state of America. “Thanks to this footage, everyone can see the brutal and unconscionable condition of the United States in the year 2015 with their own eyes,” said Hamilton County prosecutor Joe Deters, who noted that the violent nature of circumstances in America may make the footage disturbing for some to watch. “It’s stomach-turning to go frame by frame through this video and see the grotesque realities of our country unfold in such visceral detail. But it’s vitally important to have a visual record that tells the truth about this nation rather than be forced to trust the accounts of those who ...

This came out of documentation I was writing up for staff here at UTK. I apologize if it is too UTK-workflow specific.

I’m working currently on migrating a lot of our non-MARC metadata collections from older platforms using a kind of simple Dublin Core to MODS/XML (version 3.5, we’re currently looking at 3.6) that will be ingested into Islandora. That ‘kind of simple Dublin Core’ should be taken as: there was varying levels of metadata oversight over the years, and folks creating the metadata had different interpretations of the Dublin Core schema - a well-documented and well-known issue/consideration for working with such a general/flexible schema. Yes, there are guidelines from DCMI, but for on-the-ground work, if there is no overarching metadata application profile to guide and nobody with some metadata expertise (or investment) to verify that institution-wide, descriptive (or any type, for that matter) metadata fields are being used consistently, it is no surprise that folks will interpret metadata fields in different ways with an eye to their own collection/context. This issue increases when metadata collections grow over time, occur with little to no documentation, and a lot of the metadata creation is handed off to content specialists, who might then hand it off to their student workers. If you are actually reading my thoughts right now, well thanks, but also you probably know the situation I’m describing well.

Regardless, I’m not here to talk about why I think my job is important, but rather about a very particular but useful procedure and tool that make up my general migration/remediation work, which also happens to be something I’m using and documenting right now for UTK cataloger reskilling purposes. I have been working with some of the traditional MARC catalogers to help with this migration process, and so far the workflow is something like this:

1. I pull the original DC (or other) data, either from a csv file stored somewhere, or, preferably, from an existing OAI-PMH DC/XML feed for collections in (soon to be legacy) platforms. This data is stored in a GitHub repository [See note below] as the original data for both version control and “But we didn’t write this” verification purposes.
2. A cleaned data directory is made in that GitHub repo, where I put a remediation files subdirectory. I will review the original data, see if an existing, documented mapping makes sense (unfortunately, each collection usually requires separate mapping/handling), and pull the project into OpenRefine. In OpenRefine, I’ll do a preliminary ‘mapping’ (rename columns, review the data to verify my mapping as best I can without looking at the digitized objects due to time constraints). At this point, I will also note what work needs to be done in particular for that dataset. I’ll export that OpenRefine project and put it into the GitHub repo remediation files subdirectory, and also create or update the existing wiki documentation page for that collection.
3. At this point, I will hand off the OpenRefine project to one of the catalogers currently working on this metadata migration project. They are learning OpenRefine from scratch but doing a great job of getting the hang of both the tool and the mindset for batch metadata work. I will tell them some of the particular points they need to work on for that dataset, but also they are trained to check that the mapping holds according to the UTK master MODS data dictionary and MAP, as well as that controlled access points have appropriate terms taken from the selected vocabularies/ontologies/etc. that we use. With each collection they complete, I’m able to give them a bit more to handle with the remediation work, which has been great.
4. Once the catalogers are done with their remediation work/data verification, I’ll take that OpenRefine project they worked on, bring it back into OpenRefine on my computer, and run some of the reconciliation services for pulling in URIs/other related information we are currently capturing in our MODS/XML. One of the catalogers is starting to run some of these recon services herself, but it is something I’m handing over slowly because there is a lot of nuance/massaging to some of these services, and the catalogers working on this project only currently do so about 1 day a week (so it takes longer to get a feeling for this).
5. I review, do some reconciliation stuff, get the complex fields together that need to be for the transform, then export as simple XML, take that simple XML and use my UTK-standard OpenRefine XML to MODS/XML XSLT to generate MODS/XML, then run encoding/well-formed/MODS validation checks on that set of MODS/XML files.
6. Then comes the re-ingest to Islandora part, but this is already beyond the scope of what I meant this post to be.

GitHub Note: I can hear someone now: ‘Git repositories/GitHub is not made for data storage!’ Yes, yes, I know, I know. It’s a cheat. But I’m putting these things under version control for my own verification purposes, as well as using GitHub because it has a nice public interface I can point to whenever a question comes up about ‘What happened to this datapoint’ (and those questions do come up). I don’t currently, but I have had really good luck with using the Issues component of GitHub too for guiding/centralizing discussion about a dataset. Using GitHub also has had the unintended but helpful consequence of highlighting to content specialists who are creating the metadata just why we need metadata version control, and why the metadata updates get frozen during the review, enhancement and ingest process (and after that, metadata edits can only happen in the platform). But, yes, GitHub was not made for this, I know. Maybe we need dataHub. Maybe there is something else I *should* be using. Holla if you know what that is.

Okay, so I’m in step 4 right now, with a dataset that was a particular pain to remediate/migrate because the folks who did the grouping/digitization pulled together a lot of different physical objects into one digital object. This is basically the digital equivalent of ‘bound-withs’. However, the cataloger who did some of the remediation did a great job of finding, among other datapoints, the subject_geographic terms, getting them to subject_geographic, and normalizing the datapoint to a LCNAF/LCSH heading where possible. I’m about to take this and run my OpenRefine Geonames recon service against it to pull in coordinates for these geographic headings where possible. As folks seem to be interested in that recon service, I’m going to walk through that process here and now with this real life dataset.

WHERE I STOP BLABBING AND TALK ABOUT GEONAMES RECON SERVICE FINALLY

So here is that ready-for-step-4 dataset in LODRefine (Linked Open Data Refine, or OpenRefine with some Linked Data extensions baked in; I need to write more about that later):

You can see from that portion a bit of what work is going on here. What I’m going to target in on right now is the subject_geographic column, which has multiple values per record (records in this instance are made up of a number of rows. This helps centralize the reconciliation work, but will need to be changed to 1 record = 1 row before pulling out for XML transformations). Here is the column, along with a text facet view to see the values we will be reconciling against Geonames:

Look at those wonderfully consistent geographic terms, thanks to the cataloger’s work! But, some have LoC records and URIs, some don’t, some maybe have Geonames records (and so coordinates), some might not… so let’s go ahead and reconcile with Geonames first. To use the Geonames service, I already have a copy of the Geonames Recon Service on my computer, and I have updated my local machine’s code to have my own private Geonames API name. See more here: https://github.com/cmh2166/geonames-reconcile.

I’m then going to a CLI (on my work computer, just plain old Mac Terminal),

change to the directory where I have my local Geonames recon service code stored,

then type in the command ‘python reconcile.py –debug’. The Geonames endpoint should fire up on your computer now. You may get some warning notes like I have below, which means I need to do some updating to this recon service or to my computer’s dependencies installation (but am going to ignore for time being while recon service still works because, well, time is at a premium).

Note, during all of this, I already have LODRefine running in a separate terminal and the LODRefine GUI in my browser.

Alright, with all that running, lets hop back to our web browser window where LODRefine GUI is running with my dataset up. I’ve already added this Geonames as a reconciliation service, but in case you haven’t, you would still go first to the dropdown arrow for any column (I’m using the column I want to reconcile here, subject_geographic), then to Reconcile > Start Reconciling.

A dialog box like this should pop up:

I’ve already got GeoNames Reconciliation Service added, but if you don’t, click on ‘Add Standard Service’ (in the bottom left corner), then add the localhost URL that the Geonames python flask app you started up in the Terminal before is running on (for me and most standard set ups, this will be http://0.0.0.0:5000/reconcile):

I will cancel out of that because I already have it running, and then click on the existing GeoNames Reconciliation Service in the ‘Reconcile column’ dialog box. If you just added the service, you should have the same thing as me showing now upon adding the service:

There are a few type options to choose from:

• geonames/name = search for the cells’ text just in the names field in a Geonames record
• geonames/name_startWith = search for Geonames records where the label starts with the cells’ text
• geonames/name_equals = search for an exact match between the Geonames records and the cells’ text
• geonames/all = just do keyword search of Geonames records with our cells’ text.

Depending on the original data you are working with, the middle two options can return much more accurate results for your reconciliation work. However, because these are LoC-styled headings (with the mismatching of headings style with Geonames I’ve described recently in other posts as well as in the README.md for this Geonames Recon code), I’m going to go with geonames/all. If you haven’t read those other thoughts, basically, the Geonames name for Richmond, Virginia is just ‘Richmond’, with Virginia, United States, etc. noted instead in the hierarchy portion of the record. This makes sense but makes for bad matching with LoC-styled headings. Additionally, the fact that a lot of these geographic headings refer to archaeological dig sites and not cities/towns/other geopolitical entities also means a keyword search will return better results (in that it will return results at all).

Sidenote: See that ‘Also use relevant details from other columns’ part? This is something I’d love to use for future enhancements to this recon service (maybe refer to hierarchical elements there?) as well as part of a better names (either LCNAF or VIAF) recon service I’m wanting to work more on. Names, in particular, personal names and reconciliation is a real nightmare right now.

Alright, so I select ‘geonames/all’ then I click on the ‘Start reconciling’ button in the bottom right corner. Up should pop a yellow notice that reconciliation is happening. Unfortunately, you can’t do more LODRefine work while that is occuring, and depending on your dataset size, it might take a while. However, one of the benefits of using this reconciliation service (versus a few others ways that exist for reconciliation against an API in LODRefine) is speed.

Once the reconciliation work is done, up should pop a few more facet boxes in LODRefine - the judgement and the best candidate’s score boxes, as well as the matches found as hyperlinked options below each cell in the column. Any cell with a value considered a high score match to a Geonames value will be associated with and hyperlinked to that Geonames value automatically.

Before going through matches and choosing the correct ones where needed, I recommend you change the LODRefine view from rows to records - as long as the column you are reconciling in is not the first column. Changing from records to rows then editing the first column means that, once you go back to records view, the records groupings may have changed and no longer be what you intent. But for any other column, the groupings remain intact.

Also, take a second to look at the Terminal again where Geonames is running. You should see a bunch of lines showing the API query URLs used for each call, as well as a 200 response when a match is found (I’m not going to show you this on my computer as each API call has my personal Geonames API name/key in it). Just cool to see this, I think.

Back to the work in LODRefine, I’m going to first select to facet the results with judgement:none and then unselect ‘error’ in the best candidate’s score facet box.

If you’re looking at this and thinking ‘1 match? that is not really good’, well… 1. yes, there are definite further improvements needed to have Geonames and LoC-styled headings work better together, but… 2. library data has a much, much higher bar for this sort of batch work and the resultant quality/accuracy expected, so 1 auto-determined match in a set of geographic names focused on perhaps not well known archaeological sites is okay with me. Plus, the Geonames recon service is not done helping us yet.

Now you should have a list of cells with linked options below each value:

What I do now is review the options, and choose the double check box for what is the correct Geonames record to reconcile against. The double check box means that what I choose for this cell value will also be applied to all other cells in LODRefine that have that same value.

If I’m uncertain, I can also click on any of the options, and the Geonames record for that option will show up for my review. Also, for each option you select as the correct one for that cell, those relevant cells should then disappear from the visible set due to our facet choices.

Using these functionalities, I can go through the possible matches fairly quickly, and much more quickly all other work included than doing this matching entirely manually. Due to the constraints of library data’s expected quality, this sort of semi-automated, enhanced-manual reconciliation is really where a lot of this work will occur for many (but not all) institutions.

If in reviewing the matches, if there is no good match presented, you can choose ‘create new topic’ to pass through the heading as found, unreconciled with Geonames.

Now I’m done my review (which took about 5 minutes for this set), I can see that I have moved from 1 matched heading to 106 matched headings (I deselected the ‘None’ facet in the judgment box and closed the ‘best match facet’ box).

However, there are still 134 headings that were matched to nothing in Geonames. Click on that ‘none’ facet in the judgment box, and leaving the geographic_subject column text facet box up, I can do a quick perusal of what didn’t find a match, as well as check on headings that seem like should have had a match in Geonames. However, for this dataset, I see a lot of these are archaeological dig sites, which probably aren’t in Geonames, so the service worked fairly well so far. This is also how you’ll find some typos or other errors as well, and any historical changes in names that may have occured. For the facet values that I do find in Geonames, I click to edit the facet value and go ahead and add the coordinates, which is what I pull from Geonames currently (we opt to choose the LoC URI for these headings at present, but this is under debate).

Note: datasets with more standard geographic names (cities, states, etc) will have much better results doing the above described work. However, I want to show here a real life example of something I want to pull in coordinates from Geonames for, like archaeological or historical sites.

I end up adding Coordinates for 5 values which weren’t matched to Geonames either because of typos or because the site is on the border of 2 states (a situation LoC and Geonames handle differently). I fixed 7 typos as well in this review.

Now I’m done reconciling, I want to capture the Geonames Coordinates in my final value. First I close all the open facet boxes in LODRefine. Now on that subject_geographic column, I am going to click on the column header triangle/arrow and choose Edit Cells > Transform.

In the Custom text transform on column subject_geographic box that appears, in the Expression text area, I will put in the following:

if(isNonBlank(cell.recon.match.name), value + substring(cell.recon.match.name, cell.recon.match.name.indexOf(" | ")), value)

Lets break this out a bit:

• value = the cell’s original value that was then matched against Geonames.
• cell.recon.match.name = the name (and coordinates because we’re using the Geonames recon service I cobbled together) of the value we choose as a match in the reconciliation process.
• cell.recon.match.id = the URI for that matched value from the reconciliation process.
• Why isn’t there cell.recon.match.coords? Yes, I tried that, but it involves hacking the core OpenRefine recon service backend more than I’m willing to do right now
• if(test, do this, otherwise do that) = not all of the cells had a match in Geonames, so I don’t want to change those unmatched cells. The if statements then says “if there is a reconciliation match, then pull in that custom bit, otherwise leave the cell value as is.”
• substring(cell.recon.match.name, cell.recon.match.name.indexOf(“ | “)) = means I just want to pull everything in that cell.recon.match.name value after the pipe - namely, the coordinates. I am leaving the name values as is because they are currently matched against LoC for our metadata.

Why do we need to run this transform? Because although we have done reconciliation work in LODRefine, if I was to pull this data out now (say export as CSV), the reconciliation data would not come with it. LODRefine is still storing the original cell values in the cells, with the reconciliation data laid over top of it. This transform will change the underlying cell values to the reconciled values I want, where applicable.

After running the transform, you can remove the reconciliation data to see exactly what the underlying values now look like. And remember there is always the Undo tab in LODRefine if you need to go back.

What our cell values look like now:

And, ta-da! Hooray! At this point, I can shut down the Geonames reconciliation python flask app running in that terminal by going to the Terminal window it is running in and typing in cntl + C. Back in LODRefine, remember to change back from rows view to records view (links to do this are in the top left corner).

Thoughts on this process

Some may think this process seems a bit extreme for pulling in just coordinates. However…

1. Remember that this seems extreme for the first few times or when you are writing up documentation explaining it (especially if you are as verbose as I am). In practice, this takes me maybe at most 20 minutes for a dataset of this size (73 complex MODS records with 98 unique subject_geographic headings). It gets faster and easier, and is definitely more efficient still, than completely manually updates, and remains far more accurate than completely automated reconciliation options.
2. If so moved, I could pull in Geonames URIs as part of this work, which would be even better. However, because of how we handle our MODS at present, we don’t. But the retrieval of URIs and other identifiers for such datapoints is a key benefit.
3. For datasets larger than 100 quasi-complex records, this is really the only way to go at present and considering our workflows. I don’t want to give these datasets to the catalogers and ask them to add coordinates, URIs, or other reconciled information because they need to focus on the batch work on this process - checking the mappings, getting values in appropriate formats or encodings - and not manually searching each controlled access point in a record or row then copy and pasting that information from some authority source. But this is all a balancing act.
4. This process also has the added benefit of making very apparent typos and other such mistakes. Unfortunately, I’m not as aware in my quick blog ramblings.

Hope this is helpful for others.

These potato dumplings are charmingly known as "tater tots" in the regional dialect.

Read more If White People Food Were Described Like “Exotic” Food at The Toast.

vintagegal:

“The first thing a Cry-Baby girl learns: our bazooms are our weapons!” Cry-Baby (1990) dir. John Waters

The "modern supper club" is opening in the former Locke-Ober space downtown, and Thompson will be directing the beverage program.

When the storied Locke-Ober is reborn as Yvonne's, a "modern supper club" that will open "soon," diners can expect an extraordinary bar program: Will Thompson is on board as beverage director. Thompson's epic resume includes stints at Drink, Brick & Mortar, No. 9 Park, Lone Star Taco Bar, Deep Ellum, and Straight Law. The latter is a well-regarded gin and sherry bar that he developed inside of Taberna de Haro in Brookline. He also worked with O Ya's Tim and Nancy Cushman to launch their first New York City venture, the Roof at Park South.

Other previously announced staff includes chefs Tom Berry (Proprietors in Nantucket) and Juan Pedrosa (The Glenville Stops), as well as pastry chef Kate Holowchik. Co-owner Chris Jamison is also behind Lolita Cocina in Back Bay, and he's opening Yvonne's with business partner Mark Malatesta. Sox great David Ortiz, aka "Big Papi," is also a partner in the venture.

Yvonne's will feature "eclectic dishes that pay homage to Locke-Ober's classic yet internationally informed fare," according to a previous report by Boston Magazine, which includes a sexy photo of an Argentine-inspired flank-steak matambre. Keep an eye out for a secret entrance and a swanky library bar.

In hush-hush supper club fashion, the upcoming restaurant has been keeping pretty quiet on social media, but follow along on Twitter, Instagram, and Facebook in case any updates pop up.

Thursday marks the grand opening of the new Boston Public Market. It’s the first of its kind in the country — a year-round market with all of its goods sourced right here in New England.

Over 10 years in the making, the 30,000-square-foot building — originally a Big Dig building — currently houses 38 vendors, with room for more.

The market’s CEO, Liz Morningstar, gave us a tour earlier this week.

Mimi Hall, programming manager for the Trustees of the Boston Public Market, speaks Wednesday about how the market’s kitchen, tucked in the back of the building, will be used for cooking classes and community events. (Hadley Green for WBUR)

Interview Highlights

On what’s unique about the market:

The thing that is most unique about the Boston Public Market is it’s the first all-locally sourced market of its kind in the United States, so everything sold here is either produced or originates in New England. Ninety-three percent of our vendors are all from Massachusetts, so it’s incredibly local. We have 15 farms here. Of those 15 farms, nine of them are all family owned. Our closest farm is actually in East Boston.

On whether the vendors will change:

I expect they will.

People ask me, how will you know if it’s successful, or what will it be like in a year from now, and what I would say is I expect it’ll be very different. I think we’re going to have change; it’s built that way, that’s what the business plan suggests, that it should be something that is rotating as an incubator space, as a space for new product to come to market.

A selection of cheeses for sale from Jasper Hill Farm at the market (Hadley Green for WBUR)

On one of the vendors: Jasper Hill cheese:

Jasper Hill is world winning, fabulous bleu cheese. So they’ll be selling whole chunks of cheese that you would go home and use in your own kitchen, and then they’re doing grilled cheeses. So this idea of a double concept, of a whole food with a prepared item.

We’ll have online coverage of the market’s first lunch rush Thursday.

Visitors at the Boston Public Market sample Taza Chocolate. (Hadley Green for WBUR)

Related:

• It Looks Like Boston Is Finally Getting A Public Food Market
• Garden-Inspired Cooking With Kathy Gunst

Claiming police have “utilized union resources to defend brutality and anti-Blackness,” United Auto Workers Local 2865’s Black Interests Coordinating Committee (BICC), penned a letter calling on the AFL-CIO to end its affiliation with IUPA.

In its letter, the UAW affiliate states:

We, UAW Local 2865, call on the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO) to end their affiliation with the International Union of Police Associations. It is our position that this organization is inimical to both the interests of labor broadly, and Black workers in particular. Historically and contemporarily, police unions serve the interests of police forces as an arm of the state, and not the interests of police as laborers. Instead, their “unionization” allows police to masquerade as members of the working-class and obfuscates their role in enforcing racism, capitalism, colonialism, and the oppression of the working-class. We ask that the AFL-CIO recognize this history and take steps to serve the interests of its Black workers and community members.

The letter goes on to state that “police unions fail to meet the criteria of a union or a valid part of the labor movement.”

While it is true that police are workers, and thus hypothetically subject to the same kinds of exploitation as other laborers, they are also the militarized, coercive arm of the state….The police force exists solely to uphold the status quo.

Policing in the U.S. has always served the needs of colonialism, racism, and capitalism by protecting the property of those who would steal land and exploit the labor of others. Neither the property of indigenous people nor the products of the labor of both workers and slaves has ever come under protection of the institution of the police. It has only ever been the property of the powerful that the police protect. Maintaining this system of relations is the so called “order” that police have sworn to defend.

“If labor is to ever truly exert its power and challenge the corporate rule of the U.S.,” the UAW affiliate writes, “we will need to break the illusion that the police are part of the family of unions that make up organized labor.

Mad Max: Fury Road Trivia

Poor Gyro Captain.

Jon Stewart slipped unnoticed into the White House in the midst of the October 2011 budget fight, summoned to an Oval Office coffee with President Barack Obama that he jokingly told his escort felt like being called into the principal’s office.

In February 2014, Obama again requested Stewart make the trip from Manhattan to the White House, this time for a mid-morning visit hours before the president would go before television cameras to warn Russia that “there will be costs” if it made any further military intervention in Ukraine.

To engage privately with the president in his inner sanctum at two sensitive moments — previously unreported meetings that are listed in the White House visitor logs and confirmed to POLITICO by three former Obama aides — speaks volumes about Stewart and his reach, which goes well beyond the million or so viewers who tune into The Daily Show on most weeknights.

Wheaton College has taken its battle over Obamacare's birth control mandate from the courtroom to its campus.

The evangelical college in Illinois told its students last week that it would be ending the health insurance plans it had been offering them due to its case against Obama administration, the Chicago Tribune reported.

The school terminated its plan not due to the fact that it was being forced to pay for contraceptive coverage -- it is not -- but that it is in a legal battle over whether it should even have to notify the government that it is seeking a religious exemption to providing contraceptive coverage. The current policy for religious non-profits gives them an exemption, at which point the government directs insurers to provide birth control coverage through a separate policy not paid for by the non-profit.

Wheaton contends that even the act of notifying the government of its religious opposition to birth control coverage makes it complicit in providing birth control. A federal appeals court has rejected Wheaton's contention, so rather than comply with the requirement that it notify the feds, Wheaton is ending all health coverage for students.

The Drudge Report on Wednesday pondered whether Pope Francis, who has recently fallen out of favor with some conservatives, is actually the "antichrist," noting that the pope's "stand on homosexuality, Islam, capitalism, and the New World Order" fuel chatter.

Drudge links to an article on Charisma News explaining, "Why So Many People Think Pope Francis Is the Antichrist." The post asks whether Francis' role as antichrist signifies the second coming of Christ.

If Saturday night was a celebration, the days after have served as a wake. After 40 years of music T.T. The Bear’s Place hosted its last show over the weekend, and yesterday crews were busy

The post Here is the most heartbreaking photo that proves T.T. The Bear’s Place is no more appeared first on Vanyaland.

artbooksnat:

Yurikuma Arashi (ユリ熊嵐)

The memorable patterns and digital designs of Yurikuma Arashi are highlighted in the pages of Yurikuma Arashi Perfect Guide (Amazon US | JP).