Related
According to this doc: https://docs.adyen.com/developers/marketpay/marketpay-overview
Supported countries (12)
MarketPay is currently available for the following countries: Austria, Belgium, Finland, France, Germany, Ireland, Italy, the Netherlands, Portugal, Spain, the United Kingdom (including Isle of Man & Jersey), and the United States.
According to this: https://www.adyen.com/our-solution/online-payments/marketplaces
Payout 25+ countries
Which is correct and where can I see the list?
The difference here is what MarketPay supports vs the functionality of paying-out.
MarketPay includes functionality like KYC/Customer verification, funds management, as well as payout. This set of functionality is currently available in the 12 countries mentioned in the MarketPay documentation overview.
For the payout to 25+ countries, this is referencing the functionality of paying out to a bank account or card, independent of the MarketPay solution. This is represented in the docs under the third party payouts documentation
Is there any way to add different styles for columns made with column-count? I have a div which is divided into multiple columns using column-count. At a time only two columns are visible on page. I need to add margin-left to the first column and margin-right for the second column and so on.
What I need is the same spacing on both (outer and inner) sides of the pages just like book.
.main {
overflow: scroll;
width: 100%;
height: 438px;
column-gap: 160px;
columns: 2 auto;
column-fill: auto;
margin-top: 5px;
}
<div class="main">
Wikidata is a free, collaborative, multilingual, secondary database, collecting structured data to provide support for Wikipedia, Wikimedia Commons, the other wikis of the Wikimedia movement, and to anyone in the world. What does this mean? Let's look
at the opening statement in more detail: Contents 1 What does this mean? 2 How does Wikidata work? 2.1 The Wikidata repository 2.2 Working with Wikidata 3 Where to get started 4 How can I contribute? 5 There is more to come Free. The data in Wikidata
is published under the Creative Commons Public Domain Dedication 1.0, allowing the reuse of the data in many different scenarios. You can copy, modify, distribute and perform the data, even for commercial purposes, without asking for permission. Collaborative.
Data is entered and maintained by Wikidata editors, who decide on the rules of content creation and management. Automated bots also enter data into Wikidata. Multilingual. Editing, consuming, browsing, and reusing the data is fully multilingual. Data
entered in any language is immediately available in all other languages. Editing in any language is possible and encouraged. A secondary database. Wikidata records not just statements, but also their sources, and connections to other databases. This
reflects the diversity of knowledge available and supports the notion of verifiability. Collecting structured data. Imposing a high degree of structured organization allows for easy reuse of data by Wikimedia projects and third parties, and enables
computers to process and “understand” it. Support for Wikimedia wikis. Wikidata assists Wikipedia with more easily maintainable information boxes and links to other languages, thus reducing editing workload while improving quality. Updates in one language
are made available to all other languages. Anyone in the world. Anyone can use Wikidata for any number of different ways by using its application programming interface. How does Wikidata work? This diagram of a Wikidata item shows you the most important
terms in Wikidata. Wikidata is a central storage repository that can be accessed by others, such as the wikis maintained by the Wikimedia Foundation. Content loaded dynamically from Wikidata does not need to be maintained in each individual wiki project.
For example, statistics, dates, locations and other common data can be centralized in Wikidata. The Wikidata repository Items and their data are interconnected. The Wikidata repository consists mainly of items, each one having a label, a description
and any number of aliases. Items are uniquely identified by a Q followed by a number, such as Douglas Adams (Q42). Statements describe detailed characteristics of an Item and consist of a property and a value. Properties in Wikidata have a P followed
by a number, such as with educated at (P69). For a person, you can add a property to specifying where they were educated, by specifying a value for a school. For buildings, you can assign geographic coordinates properties by specifying longitude and
latitude values. Properties can also link to external databases. A property that links an item to an external database, such as an authority control database used by libraries and archives, is called an identifier. Special Sitelinks connect an item
to corresponding content on client wikis, such as Wikipedia, Wikibooks or Wikiquote. All this information can be displayed in any language, even if the data originated in a different language. When accessing these values, client wikis will show the
most up-to-date data. Item Property Value Q42 P69 Q691283 Douglas Adams educated at St John's College Working with Wikidata There are a number of ways to access Wikidata using built-in tools, external tools, or programming interfaces. Wikidata Query
and Reasonator are some of the popular tools to search for and examine Wikidata items. The tools page has an extensive list of interesting projects to explore. Client wikis can access data for their pages using a Lua Scribunto interface. You can retrieve
all data independently using the Wikidata API. Where to get started The Wikidata tours designed for new users are the best place to learn more about Wikidata. Some links to get started: Set your user options, especially the 'Babel' extension, to choose
your language preferences Help with missing labels and descriptions Help with interwiki conflicts and constraint violations Improve a random item Help translating How can I contribute? Go ahead and start editing. Editing is the best way to learn about
the structure and concepts of Wikidata. If you would like to gain understanding of Wikidata's concepts upfront, you may want to have a look at the help pages. If you have questions, please feel free to drop them in the project chat or contact the development
team. There is more to come Wikidata is an ongoing project that is under active development. More data types as well as extensions will be available in the future. You can find more information about Wikidata and its ongoing development on the Wikidata
page on Meta. Subscribe to the the Wikidata mailing list to receive up-to-date information about the development and to participate in discussions about the future of the project. North Korea conducted its sixth nuclear test on 3 September 2017, according
to Japanese and South Korean officials. The Japanese Ministry of Foreign Affairs also concluded that North Korea conducted a nuclear test.[6] The United States Geological Survey reported an earthquake of 6.3-magnitude not far from North Korea's Punggye-ri
nuclear test site.[7] South Korean authorities said the earthquake seemed to be artificial, consistent with a nuclear test.[6] The USGS, as well as China's earthquake administration, reported that the initial event was followed by a second, smaller,
earthquake at the site, several minutes later, which was characterized as a collapse of the cavity.[8][9] North Korea claimed that it detonated a hydrogen bomb that can be loaded on to an intercontinental ballistic missile (ICBM) with great destructive
power.[10] Photos of North Korean leader Kim Jong-un inspecting a device resembling a thermonuclear weapon warhead were released a few hours before the test.[11] Contents 1 Yield estimates 2 Reactions 3 See also 4 References Yield estimates According
to estimates of Kim Young-Woo, the chief of the South Korean parliament's defense committee, the nuclear yield was equivalent to about 100 kilotons of TNT (100 kt). "The North's latest test is estimated to have a yield of up to 100 kilotons, though
it is a provisional report," Kim Young-Woo told Yonhap News Agency.[2] On 3 September, South Korea’s weather agency, the Korea Meteorological Administration, estimated that the nuclear blast yield of the presumed test was between 50 to 60 kilotons.[3]
On 4 September, the academics from University of Science and Technology of China[12] have released their findings based on seismic results and concluded that the Nuclear Test Location is at 41°17′53.52″N 129°4′27.12″E on 03:30 UTC which is only a few
hundred meters apart from the previous 4 tests (2009, 2013, January 2016 and September 2016) with the estimated yield at 108.1 ± 48.1 kt. In contrast, the independent seismic monitoring agency NORSAR estimated that the blast had a yield of about 120
kilotons, based on a seismic magnitude of 5.8.[4] The Federal Institute for Geosciences and Natural Resources in Germany estimates a higher yield at "a few hundred kilotons" based on a detected tremor of 6.1 magnitude.[5] Reactions South Korea, China,
Japan, Russia and members of the ASEAN[13] voiced strong criticism of the nuclear test.[14] US President Donald Trump tweeted "North Korea has conducted a major Nuclear Test. Their words and actions continue to be very hostile and dangerous to the United
States".[15][16] Trump was asked whether the US would attack North Korea and replied, "We'll see".[17] On September 3, U.S. Defense Secretary James Mattis warned North Korea, saying that the country would be met with a "massive military response" if
it threatened the United States or its allies.[18] The United Nations Security Council will meet in an open emergency meeting on September 4, 2017 at the request of the US, South Korea, Japan, France and the UK.[19] Federal Institute for Geosciences
and Natural Resources From Wikipedia, the free encyclopedia (Redirected from Bundesanstalt für Geowissenschaften und Rohstoffe) Federal Institute for Geosciences and Natural Resources Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) Agency overview
Headquarters Hanover, Germany Employees 795 in 2013 Website www.bgr.bund.de The Federal Institute for Geosciences and Natural Resources (Bundesanstalt für Geowissenschaften und Rohstoffe or BGR) is a German agency within the Federal Ministry of Economics
and Technology. It acts as a central geoscience consulting institution for the German federal government.[1] The headquarters of the agency is located in Hanover and there is a branch in Berlin. Early 2013, the BGR employed a total of 795 employees.
The BGR, the State Authority for Mining, Energy and Geology and the Leibniz Institute for Applied Geophysics form the Geozentrum Hanover. All three institutions have a common management and infrastructure, and complement each other through their interdisciplinary
expertise.
</div>
Here is the JSFiddle for testing link
I am wondering if there is some sort of "standard" for storing US addresses in a database? It seems this is a common task, and there should be some sort of a standard.
What I am looking for is a specific schema of how the database tables should work and interact, already in third normal form, including data types (MySQL). A good UML document would work.
Maybe I'm just being lazy, but this is a very common task, and I am sure someone has published an efficient way to do this somewhere. I just don't know where to look and Google isn't helping. Please point me to the resource. Thanks.
EDIT
Although this is more of a general question, I would like to clarify my specific needs.
Addresses will be used to specify road addresses of locations of events. These addresses will need to be in a format that can be best broken down and searched, and also used by any third-party applications I may end up linking my data source to.
ALSO. Data will be geo-coded (long, lat) on entry and stored separately, so it must fit the (yet undecided) protocol of whatever geocoder / application / library does that.
For international addresses, refer to the Universal Postal Union's Postal Addressing Systems database.
For U.S. addresses, refer to USPS Publication 28 "Postal Addressing Standards".
The USPS wants the following unpunctuated address components concatenated on a single line:
house number
predirectional (N, SE, etc.)
street
suffix (AVE, BLVD, etc.)
postdirectional (SW, E, etc.)
unit (APT, STE, etc.)
apartment/suite number
E.g. 102 N MAIN ST SE APT B
If you keep the entire address line as a single field in your database, input and editing is easy, but searches can be more difficult (eg, in the case SOUTH EAST LANE is the street EAST as in S EAST LN or is it LANE as in SE LANE ST?).
If you keep the address parsed into separate fields, searches for components like street name or apartments become easier, but you have to append everything together for output, you need CASS software to parse correctly, and PO boxes, rural route addresses, and APO/FPO addresses have special parsings.
A physical location with multiple addresses at that location is either a multiunit building, in which case letters/numbers after units like APT and STE designate the address, or it's a Commercial Mail Receiving Agency (eg, UPS store) and a maildrop/private mailbox number is appended (like 100 MAIN ST STE B PMB 102), or it's a business with one USPS delivery point and mail is routed after USPS delivery (which usually requires a separate mailstop field which the company might need but the USPS won't want on the address line).
A contact with more than one physical address is usually a business or person with a street address and a PO box. Note that it's common for each address to have a different ZIP code.
It's quite typical that one business transaction might have a shipping address and a billing address (again, with different ZIP codes). The information I keep for EACH address is:
name prefix (DR, MS, etc)
first name and initial
last name
name suffix (III, PHD, etc)
mail stop
company name
address (one line only per Pub 28 for USA)
city
state/province
ZIP/postal code
country
I typically print mail stops somewhere between the person's name and company because the country contains the state/ZIP which contains the city which contains the address which contains the company which contains the mail stop which contains the person. I use CASS software to validate and standardize addresses when entered or edited.
First, as a person who spend most of there professional day working with addresses, they are hard to manage from a data perspective.
If you ask 5 people what address they live at; you will find that you get 5 different answers. While you and I can tell that 123 Main Street Apt 1 and Apt 1 123 Main Street
are the same address, the database program will have a challenge.
If you are using United States centric addresses CASS certified software from almost any vendor will standardize your addresses reasonably well. I would recommend a simple format as follows:
Address 1
Address 2
Address 3
City
State
Zip
Zip+4 (I would carry this so lookups are easier when checking for duplicates)
However, if you want a universal address I would look at the ADIS standard from IdeaAlliance. This standard can be used to breakdown (parse) addresses from almost any country into the relevant parts. Then they can be put back together using templates/components based on the Universal Postal Union standards (UPU S42 Standard on International Postal Address Components and Templates).
The big plus of this format is that addresses that dont exist in a postal database like CASS can be entered and stored as separate parts.
Very similar questions have been asked before.
Addresses are messy - at best.
It partly depends on what you want to do with the addresses. If you're going to use them to mail thing to people, then you simply need to record the image that will appear on the address label in a convenient form. If you're going to analyze the address, you have to work a lot harder.
Remember that the first time you have to deal with someone outside the US, all previous rules go astray. You may be strictly US-only, but beware.
I looked into this a while ago, but for international addresses. I didn't find much in the way of a consensus. However, for the US, I found the succinctly named United States Thoroughfare, Landmark, and Postal Address Data Standard (Draft):
http://www.fgdc.gov/standards/projects/FGDC-standards-projects/street-address/index_html
I don't think that they actually provide any specific database schema ideas, but it might be a good starting point.
First, the "best" means of storing an address depends greatly on how it will be used. Is it just for reference or searches on say city? Do you plan on addressing envelopes? Are you going to integrate with a shipping system like FedEx or UPS? Will you store non-US addresses? Once you get into the realm of integrating with something that ships, you should start looking at CASS. This is a specification for handling the USPS addresses. There are applications out there that are CASS certified which will store and verify addresses. Thus, the second best practice would be to try to avoid reinventing the wheel and see if there is a system out there that will solve your problem especially if you are going to go international. You want to leverage the fact that someone else has worked out all the details about how to properly and efficiently store addresses for many countries around the world instead of having to do that investigation yourself.
I've had to try to do this before and I'd found this document that gives you some pointers. I ended up shelving my schema since my application does have to deal with international addresses.
I use the downloadable Geonames database for all countries, states, counties and cities in the world, but I wonder if there is a database for streets?
So you could pick: country -> state/department/district -> (county/region) -> city -> street in whatever country you like.
Because when I do a search for a street in Google Maps I can see all the upper levels (country/region/city). Is there a database you could download for MySQL for this?
There has to be a database for this, cause there are always national companies that provide this kind of information. Where did they get it from?
Have you checked out OpenStreetMap? It is free and has a export screen that lets you download the data in XML and other formats.
Those concerned with the accruacy of the OpenStreetMap data may want to read what ITO has to say about OpenStreetMap's data for Haiti.
Enter OpenStreetMap, the wiki map of the world, CrisisMappers and an impromptu community of volunteers who collaborated to produce the most authoritative map of Haiti in existence.
If you have 5 minutes you may want to watch this TED video by Tim Berners-Lee talking about what is being done with OpenStreetMap data.
You're looking for Navteq or Tele Atlas.
They will charge lots of money.
The US Census Bureau provides what they call TIGER files, which might help you out for the US anyway... As far as freely available worldwide data I seriously doubt you're gonna find much, but many governments probably provide something similar to the TIGER files. Good luck.
I think one good solution would be Listreet
Samples seems to contain country, region, city, streets and even elevation with longitude and latitude
Prices are fair and the team behind is responsive
I have a system where users need to enter addresses. I am trying to limit duplicates of course and something I started noticing was becoming a big problem was some users putting in "Road" and others "Rd", therefore duplicates were creeping in.
I looked up the list of USPS street suffix abbreviations but I still have a question which I can't find an answer to. Can I replace all words in a street address with the USPS standard abbreviation? An example would be "123 Forest Hill Road". If I were to replace it with the abbreviations it would then be "123 Frst Hl Rd" or does the "street suffix" that USPS is referring to mean they only want you to make go as far as "123 Forest Hill Rd"?
USPS has an API that can get you properly formatted addresses.
You would have to ask the USPS to be sure, but I imagine that your app and data would be in trouble if you started replacing "123 Forest Hill Rd" with "123 Frst Hl Rd".
I have done some work with addresses and let me tell you it is very complicated and time consuming to do even remotely correctly. In most cases you would be better off making use of existing packages out there. For example, you would be surprised what you can achieve with a few simple calls to the free Google Maps API.
Can you avoid the whole problem by expanding all of the terms rather than attempting to abbreviate any?
On the duplicates, just wondering if you'd be better to make the Users choose from a drop-down of Address Types. Take it out of the User's hands.
On the abbreviation, are you asking this because USPS needs the Address in some specific format? Just wondering what purpose there is in the abbreviating. Apologies if I've missed the mark.
You could also take a look at the USPS Postal Addressing Standards which has explanation of the preferred and acceptable formats for various address examples.
http://pe.usps.gov/text/pub28/pub28c2_toc.htm
In the example case, the relevant section is 23 Delivery Address Line.
http://pe.usps.gov/text/pub28/pub28c2_012.htm
The trouble with trying to expand/contract addresses yourself is that oftentimes abbreviations can be part of the street or even city name. For example: "100 Avenue A" where Avenue isn't supposed to be abbreviated. Or "900 St Louis Loop". In this case St don't mean street, it means Saint.
Within the USA, there is a component of a certificated address called a delivery point barcode (DPBC). It's a unique 12-digit value that can serve as the unique identifier of an address. To get this value you'll want to use an address verification or address standardization web service API, which can cost about $20/mo depending upon the volume of requests you make to it. Using this you can easily prevent duplicates or do fraud prevention/detection, etc.
In the interest of full disclosure, I'm the founder of SmartyStreets. We offer just such an address verification web service API called LiveAddress. You're more than welcome to contact me personally with any questions you have.