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I am looking for suggestions on what tools could be used for the following scenarios about music feature extraction and visualization (on my Mac):
identify and group notes in a score (from different voices/instruments) that sound concurrently (even if they are attacked in different time offsets, though sound at some point together due to different duration lengths); then connect them graphically (e.g. on a score representation, with a line connecting them)
identify melodic and accompanying parts (assigned to different voices/instruments, perhaps interchangeably within the same voice/instrument)
extract initial tonality and following modulations; then map all extracted tonalities on a scale based on the circle of 5ths (where 0 is the initial tonality, -1 is one 5th lower, +1 one 5th higher, etc.)
I have been thinking of using music21 (the music works I am interested in are part of its corpus), but I am not sure if this is the right way to go. Are there also other tools (e.g. jSymbolic2??) that could help?
And what about visualization? Could the above scenarios be visually "solved" within music21 or would I need an additional tool, like D3.js (which I have briefly used in the past)?
If you would have an advice on any of the above scenarios, that would help me a lot! Thanks, Ilias
Is there open data format for representing such GIS data as roads, localities, sublocalities, countries, buildings, etc.
I expect that format would define address structure and names for components of address.
What I need is a data format to return in response to reverse geocoding requests.
I looked for it on the Internet, but it seems that every geocoding provider defines its own format.
Should I design my own format?
Does my question make any sense at all? (I'm a newbie to GIS).
In case I have not made myself clear I don't look for such data formats as GeoJSON, GML or WKT, since they define geometry and don't define any address structure.
UPD. I'm experimenting with different geocoding services and trying to isolate them into separate module. I need to provide one common interface for all of them and I don't want to make up one more data format (because on the one hand I don't fully understand domain and on the other hand the field itself seems to be well studied). The module's responsibility is to take partial address (or coordinates) like "96, Dubininskaya, Moscow" and to return data structure containing house number (96), street name (Dubininskaya), sublocality (Danilovsky rn), city (Moscow), administrative area (Moskovskaya oblast), country (Russia). The problem is that in different countries there might be more/less division (more/less address components) and I need to unify these components across countries.
Nope there is not unfortunately.
Why you may ask
Beacuse different nations and countries have vastly different formats and requirements for storing addresses.
Here in the UK for example, defining a postcode has quite a complex set of rules, where as ZIP codes in the US, are 4 digit numerical prefixed with a simple 2 letter state code.
Then you have to consider the question what exactly constitutes an address? again this differences not just from country to country, but some times drastically within the same territory.
for example: (Here in the UK)
Smith and Sons Butchers
10 High street
Some town
Mr smith
10 High street
Some town
The Occupier
10 High Street
Some Town
Smith and Sons Butchers
High Street
Some Town
Are all valid addresses in the UK, and in all cases the post would arrive at the correct destination, a GPS however may have trouble.
A GPS database might be set up so that each building is a square bit of geometry, with the ID being the house number.
That, would give us the ability to say exactly where number 10 is, which means immediately the last look up is going to fail.
Plots may be indexed by name of business, again that s fine until you start using person names, or generic titles.
There's so much variation, that it's simply not possible to create one unified format that can encompass every possible rule required to allow any application on the planet to format any geo-coded address correctly.
So how do we solve the problem?
Simple, by narrowing your scope.
Deal ONLY with a specific set of defined entities that you need to work with.
Hold only the information you need to describe what you need to describe (Always remember YAGNI* here)
Use standard data transmission formats such as JSON, XML and CSV this will increase your chances of having to do less work on code you don't control to allow it to read your data output
(* YAGNI = You ain't gonna need it)
Now, to dig in deeper however:
When it comes to actual GIS data, there's a lot of standard format files, the 3 most common are:
Esri Shape Files (*.shp)
Keyhole mark up Language (*.kml)
Comma separated values (*.csv)
All of the main stay GIS packages free and paid for can work with any of these 3 file types, and many more.
Shape files are by far the most common ones your going to come across, just about every bit of Geospatial data Iv'e come across in my years in I.T has been in a shape file, I would however NOT recommend storing your data in them for processing, they are quite a complex format, often slow and sequential to access.
If your geometry files to be consumed in other systems however, you can't go wrong with them.
They also have the added bonus that you can attach attributes to each item of data too, such as address details, names etc.
The problem is, there is no standard as to what you would call the attribute columns, or what you would include, and probably more drastically, the column names are restricted to UPPERCASE and limited to 32 chars in length.
Kml files are another that's quite universally recognized, and because there XML based and used by Google, you can include a lot of extra data in them, that technically is self describing to the machine reading it.
Unfortunately, file sizes can be incredibly bulky even just for a handful of simple geometries, this trade off does mean though that they are pretty easy to handle in just about any programming language on the planet.
and that brings us to the humble CSV.
The main stay of data transfer (Not just geo-spatial) ever since time began.
If you can put your data in a database table or a spreadsheet, then you can put it in a CSV file.
Again, there is no standards, other than how columns may or may not be quoted and what the separation points are, but readers have to know ahead of time what each column represents.
Also there's no "Pre-Made" geographic storage element (In fact there's no data types at all) so your reading application, also will need to know ahead of time what the column data types are meant to be so it can parse them appropriately.
On the plus side however, EVERYTHING can read them, whether they can make sense of them is a different story.
Would OCR Software be able to reliably translate an image such as the following into a list of values?
UPDATE:
In more detail the task is as follows:
We have a client application, where the user can open a report. This report contains a table of values.
But not every report looks the same - different fonts, different spacing, different colors, maybe the report contains many tables with different number of rows/columns...
The user selects an area of the report which contains a table. Using the mouse.
Now we want to convert the selected table into values - using our OCR tool.
At the time when the user selects the rectangular area I can ask for extra information
to help with the OCR process, and ask for confirmation that the values have been correct recognised.
It will initially be an experimental project, and therefore most likely with an OpenSource OCR tool - or at least one that does not cost any money for experimental purposes.
Simple answer is YES, you should just choose right tools.
I don't know if open source can ever get close to 100% accuracy on those images, but based on the answers here probably yes, if you spend some time on training and solve table analisys problem and stuff like that.
When we talk about commertial OCR like ABBYY or other, it will provide you 99%+ accuracy out of the box and it will detect tables automatically. No training, no anything, just works. Drawback is that you have to pay for it $$. Some would object that for open source you pay your time to set it up and mantain - but everyone decides for himself here.
However if we talk about commertial tools, there is more choice actually. And it depends on what you want. Boxed products like FineReader are actually targeting on converting input documents into editable documents like Word or Excell. Since you want actually to get data, not the Word document, you may need to look into different product category - Data Capture, which is essentially OCR plus some additional logic to find necessary data on the page. In case of invoice it could be Company name, Total amount, Due Date, Line items in the table, etc.
Data Capture is complicated subject and requires some learning, but being properly used can give quaranteed accuracy when capturing data from the documents. It is using different rules for data cross-check, database lookups, etc. When necessary it may send datafor manual verification. Enterprises are widely usind Data Capture applicaitons to enter millions of documents every month and heavily rely on data extracted in their every day workflow.
And there are also OCR SDK ofcourse, that will give you API access to recognition results and you will be able to program what to do with the data.
If you describe your task in more detail I can provide you with advice what direction is easier to go.
UPDATE
So what you do is basically Data Capture application, but not fully automated, using so-called "click to index" approach. There is number of applications like that on the market: you scan images and operator clicks on the text on the image (or draws rectangle around it) and then populates fields to database. It is good approach when number of images to process is relatively small, and manual workload is not big enough to justify cost of fully automated application (yes, there are fully automated systems that can do images with different font, spacing, layout, number of rows in the tables and so on).
If you decided to develop stuff and instead of buying, then all you need here is to chose OCR SDK. All UI you are going to write yoursself, right? The big choice is to decide: open source or commercial.
Best Open source is tesseract OCR, as far as I know. It is free, but may have real problems with table analysis, but with manual zoning approach this should not be the problem. As to OCR accuracty - people are often train OCR for font to increase accuracy, but this should not be the case for you, since fonts could be different. So you can just try tesseract out and see what accuracy you will get - this will influence amount of manual work to correct it.
Commertial OCR will give higher accuracy but will cost you money. I think you should anyway take a look to see if it worth it, or tesserack is good enough for you. I think the simplest way would be to download trial version of some box OCR prouct like FineReader. You will get good idea what accuracy would be in OCR SDK then.
If you always have solid borders in your table, you can try this solution:
Locate the horizontal and vertical lines on each page (long runs of
black pixels)
Segment the image into cells using the line coordinates
Clean up each cell (remove borders, threshold to black and white)
Perform OCR on each cell
Assemble results into a 2D array
Else your document have a borderless table, you can try to follow this line:
Optical Character Recognition is pretty amazing stuff, but it isn’t
always perfect. To get the best possible results, it helps to use the
cleanest input you can. In my initial experiments, I found that
performing OCR on the entire document actually worked pretty well as
long as I removed the cell borders (long horizontal and vertical
lines). However, the software compressed all whitespace into a single
empty space. Since my input documents had multiple columns with
several words in each column, the cell boundaries were getting lost.
Retaining the relationship between cells was very important, so one
possible solution was to draw a unique character, like “^” on each
cell boundary – something the OCR would still recognize and that I
could use later to split the resulting strings.
I found all this information in this link, asking Google "OCR to table". The author published a full algorithm using Python and Tesseract, both opensource solutions!
If you want to try the Tesseract power, maybe you should try this site:
http://www.free-ocr.com/
Which OCR you are talking about?
Will you be developing codes based on that OCR or you will be using something off the shelves?
FYI:
Tesseract OCR
it has implemented the document reading executable, so you can feed the whole page in, and it will extract characters for you. It recognizes blank spaces pretty well, it might be able to help with tab-spacing.
I've been OCR'ing scanned documents since '98. This is a recurring problem for scanned docs, specially for those that include rotated and/or skewed pages.
Yes, there are several good commercial systems and some could provide, once well configured, terrific automatic data-mining rate, asking for the operator's help only for those very degraded fields. If I were you, I'd rely on some of them.
If commercial choices threat your budget, OSS can lend a hand. But, "there's no free lunch". So, you'll have to rely on a bunch of tailor-made scripts to scaffold an affordable solution to process your bunch of docs. Fortunately, you are not alone. In fact, past last decades, many people have been dealing with this. So, IMHO, the best and concise answer for this question is provided by this article:
https://datascience.blog.wzb.eu/2017/02/16/data-mining-ocr-pdfs-using-pdftabextract-to-liberate-tabular-data-from-scanned-documents/
Its reading is worth! The author offers useful tools of his own, but the article's conclusion is very important to give you a good mindset about how to solve this kind of problem.
"There is no silver bullet."
(Fred Brooks, The Mitical Man-Month)
It really depends on implementation.
There are a few parameters that affect the OCR's ability to recognize:
1. How well the OCR is trained - the size and quality of the examples database
2. How well it is trained to detect "garbage" (besides knowing what's a letter, you need to know what is NOT a letter).
3. The OCR's design and type
4. If it's a Nerural Network, the Nerural Network structure affects its ability to learn and "decide".
So, if you're not making one of your own, it's just a matter of testing different kinds until you find one that fits.
You could try other approach. With tesseract (or other OCRS) you can get coordinates for each word. Then you can try to group those words by vercital and horizontal coordinates to get rows/columns. For example to tell a difference between a white space and tab space. It takes some practice to get good results but it is possible. With this method you can detect tables even if the tables use invisible separators - no lines. The word coordinates are solid base for table recog
We also have struggled with the issue of recognizing text within tables. There are two solutions which do it out of the box, ABBYY Recognition Server and ABBYY FlexiCapture. Rec Server is a server-based, high volume OCR tool designed for conversion of large volumes of documents to a searchable format. Although it is available with an API for those types of uses we recommend FlexiCapture. FlexiCapture gives low level control over extraction of data from within table formats including automatic detection of table items on a page. It is available in a full API version without a front end, or the off the shelf version that we market. Reach out to me if you want to know more.
Here are the basic steps that have worked for me. Tools needed include Tesseract, Python, OpenCV, and ImageMagick if you need to do any rotation of images to correct skew.
Use Tesseract to detect rotation and ImageMagick mogrify to fix it.
Use OpenCV to find and extract tables.
Use OpenCV to find and extract each cell from the table.
Use OpenCV to crop and clean up each cell so that there is no noise that will confuse OCR software.
Use Tesseract to OCR each cell.
Combine the extracted text of each cell into the format you need.
The code for each of these steps is extensive, but if you want to use a python package, it's as simple as the following.
pip3 install table_ocr
python3 -m table_ocr.demo https://raw.githubusercontent.com/eihli/image-table-ocr/master/resources/test_data/simple.png
That package and demo module will turn the following table into CSV output.
Cell,Format,Formula
B4,Percentage,None
C4,General,None
D4,Accounting,None
E4,Currency,"=PMT(B4/12,C4,D4)"
F4,Currency,=E4*C4
If you need to make any changes to get the code to work for table borders with different widths, there are extensive notes at https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html
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I'm having to design & develop UI for a Point of Sale (POS) system.
There are obvious features that need to be included, like product selection & quantity, payment method, tender amount, user login (as many users will use one terminal), etc.
My question is related more towards the UI design aspect of developing this system.
How should UI features/controls be positioned, sized?
Is there a preferred layout?
Are their colours I should be avoiding?
If you know of any resources to guide me, that would also help.
The reason this is critical to me as I am aware of the pressurized environment in which POS systems are used & I want to make the process as (i) quick, (ii) simple to use and (iii) result driven as possible for the user to service customers.
All answers, info & suggestions welcome.
Thanks.
P.s. If you could mention the "playoff" between controls that would also be appreciated (i.e. if touch screen a keypad control is provided, but if also supporting keyboard & mouse input how do you manage the keypad & UI space effectively?)
A couple of thoughts from a couple of projects I've worked with:
For the touch screen ensure that each button can be pressed by someone with "fat fingers" as easily as smaller ones (some layouts encourage the use of thumbs at particular locations). Also highlight each button when it is pressed (with a slow-ish fade if you have spare CPU cycles).
Bigger grids are better than smaller ones. The numeric pad should always be in the same place (often the bottom right). The Enter/Tender/etc. "transaction" keys should be bigger than the individual numeric keys - (1) make it more obvious where it is, (2) it will be pressed more often than other screen areas and will wear out (a bigger area will last longer on average; this was more important with older style touch screens; newer technology is more resilient).
Allow functions/SKUs to be reassigned to different grid positions; the layout that works well for one store will likely be wrong for a slightly different one.
Group related functions by colour, but use excellent contrasts. Make sure that the fore/back combination looks good at all angles (some LCDs "bleed" colours left-to-right and/or top-to-bottom angles).
Positive touch screen feedback with sounds needs to have configurable volume and sound sets. Muted tones might be better in an quieter upmarket store, but "perky" sounds are better in a clothing store with louder background music/noise, etc.
Allow the grid size to be specified in percentages or "grid-block units" instead of pixels and draw everything with vectors, etc. since some hardware combinations may have LCDs with better resolution. (One system I worked on was originally specified as 640x480 but shipped at 1280x1024, so my design pre-planning saved a lot of rework later.)
And of course look at the ready-made solutions first (especially if you can get demo software/hardware for evaluation). Although they can be expensive they've often implemented a lot of things that'll you'll have to work through later, and may be cheaper in the long run, even after creating custom add-ons for your system.
Also:
Our UI supported a normal keyboard/mouse combo too (the touchable buttons were just standard button controls sized appropriately). If you pressed a number key it would trigger the same event as clicking the screen-pad button; other hotkeys were mapped to often used button commands (Enter, etc).
If run on a non-POS desktop (e.g. backoffice) the window could be resized too (the "POS desktop" maintained the same aspect ratio, adding dead space at the sides if needed). A standard top menu was available for additional administrative tasks, reporting, etc.
The design allowed everyone to build and test the UI before the associated hardware was finalized. And standard UI testing tools would work too.
Even More:
Our barcode scanners were serial/USB rather than keyboard-like, so each packet from the device raised a comms event. The selected "scanner type" driver class used the most secure formatting that the device could give us - some can supply prefix, suffix and/or checksum characters if programmed correctly - and then stripped this before handing the code up to the application.
The system made a "bzzzt" noise when the barcode couldn't be used (e.g. while cash drawer is open).
This design also avoided the need to set the keyboard focus to a specific entry area.
A tip: if the user is manually entering a barcode via the keypad, and hasn't completed it by pressing Enter, and then attempts to scan another barcode, it should beep instead, so the user can accept or cancel the pending item first.
Aggregated POS Design Guidelines
Based on the above and other literature, here is my list of guidelines for POS design.
[it would be nice if we grew this list further]
User Performance Priorities (in order):
efficiency (least time to transaction conclusion)
effectiveness (accurate info & output)
user satisfaction (based on first 2 in work context)
learning time (reduce time to learn system by making it simple)
GUIDELINES
Flexible Transaction Building - don't force a sequence to transaction wher possible. Place product orders in any order & allow them to be changed to a point.
Optimise Transaction Rate - allow a user to complete a transaction as quickly as possible (least clicks are not really the issue as more clicks could mean larger value of transaction, which makes business sense)
Support Handedness / Dexterity - most users have a dominant hand and a weaker hand in terms of dexterity. Allow the UI to be customised (on a single click) for handedness. my example: a L->R / R->L toggle button which moves easy features like "OK", "Cancel" in nearer proximity to weaker hand.
Constant Feedback - provide snapshot feedback which describes current state of the transaction and calculated result of transaction (NB: accounts) before & after committing a transaction.
Control "Volume" - control volume refers to the colour saturation/contrast, prominence of positioning and size of a control. Design more frequently used controls to have larger "volumes" relative to less frequently used controls. e.g. "Pay" button larger than "cancel" button. E.g. High contrast & greater colour saturation increase volume.
Target Findability - finding & selecting targets (item, numeric key) is key to efficiency. Group related controls (close proximity), place controls on screen edges (screen edge traps pointer), emphasise control amplitude (this dimension emphasises users normal plain of motion) and colour coding make finding & selecting targets more efficient.
Avoid Clutter - too many options limits control volume and reduces findability.
Use Plain Text - avoid abbreviations as much as possible (only use standard abbreviations e.g. size: S, M, L, etc.). This is especially true for product lookup.
Product Lookup - support shortcuts for regular orders (i.e. burger meal), categorised browsing & item name search (least ordered items). Consider include a special item: this is any item where the user types what is wanted (i.e. specific whiskey order) - this requires pricing though.
Avoid User Burden - the user should be able to read answers to customer questions from the UI. So provide regularly requested/prioritised feedback for transaction (i.e. customer asks: "what will be the the outstanding balance on my account if I buy this item?" It should appear in UI already)
Conversational Ordering - customer drives the ordering not the system. So allows item selection to be non-sequential.
Objective Focused - the purpose of POS is to conclude the transaction from a business perspective. Always make transaction conclusion possible immediately with "Pay" button. If clicked, any incomplete items will be un-done: user then read order back before requesting cash/credit card)
Personas - there are different categories (personas) of users of POS systems like (i) Clerk/Cashier and (ii) Manager. The UI should present the relevant options to that logged-in persona according to these guidelines i.e. Cashier: large volume on transaction building controls; Manager: large volume on transaction/user management controls.
Touch Screens - (i) allow for touch input with generally larger controls to supported a large finger tip as pointer. (ii) Provide proprioceptive feedback - this is feedback that indicate the control pushed (it should have a short delay on it fade: user finger will be in the way initially). (iii) Auditory Feedback (optional) - this helps with feedback especially with regards errors in pressurised environment.
User Training - users must be trained to understand business protocol & how the POS supports that protocol. They are the one's driving the system. Also, speak to POS users to design & enhance your system - again they are experienced users of the POS system
Context Analysis - a thorough analysis of the context of use for your POS system should be performed to best implement the POS heuristics mentioned above effectively. Understanding the user (human factors), the tasks (frequency, duration, stress factors, etc.) and environment (lighting, hardware, space layout, etc.) should be comprehensively conducted during design and should not be assumed. Get your hands dirty & get into the users work space!! That way you can develop something your specific users can use effectively, efficiently and satisfactorily
I hope this helps everyone.
To all respondents, I really appreciate your feedback! Please give me more wrt to this answer. Thanks
I ran across this question, and I thought I'd add my two cents since some of my work has been mentioned here.
I agree with most of what's been said, but it's important to remember that most everything mentioned represents heuristics. That means that while they're good principles to follow, there are likely times when (a) specific rules should be broken, and (b) there will be contradictions between rules. The trick is being able to weigh conflicting principles and apply them to the appropriate degrees (as you noted in a previous comment).
In the end, it's a matter of balancing the business requirements and user needs in a way that produces optimal results. And in the real world, I find that this can never be achieved through heuristics alone.
Here's an example: I recently finished POS designs for Subway, Wendy's, and Starbucks (see Case Studies at POSDesigns.com). All of these designs used solid heuristics, but all of them came out very, very different because of differences in the business goals and requirements, the users' needs and background, the environment in which they work, the technology being used, and a whole host of other differences.
You can never create a great design in a vacuum. For each of the clients mentioned above, I traveled around to a lot of different types of stores in multiple countries to get a feel for how the users' worked, how the systems would be used, how customers ordered, etc. All this information - along with sales and other data provided by the company - was invaluable in creating a highly usable solution.
Here's another example: Guideline #3 you provide previously ("Support Handedness / Dexterity") is fine as a heuristic (though I have to say that I question the conclusion of swapping simply OK/Cancel). But in visiting Subway stores, we discovered that in that context, the location of the register actually plays a greater role in the hand employees prefer.
In other words, registers that were squished against a wall on the right side tended to produce left-handed users, even when the users were right-handed for every other task. This had implications for the way we allowed the UI to be flip-flopped...and who had control of it. There are tons of examples like that, but we never could have achieved the gains that the user interfaces have produced - like 90% reduction in voids, near zero training, increased speed, accuracy, and check sizes, etc. - by following heuristics alone.
One more point (sorry...you've got me going now :-). Many times heuristics are incomplete without more data as to how to apply them. Consider your guideline #11, "Conversational Ordering". There's much more to this guideline than just providing flexibility in order entry. For instance, one of the many things you have to consider is that not all paths should be presented as equally probable.
We analyzed the way Starbucks' customers ordered in various locations across the United States and United Kingdom. Then, we optimized the system for the most commonly spoken patterns. If we had allowed all paths to have the same "volume", we would have sacrificed usability in other areas, since the design would have appeared more cluttered. The new POS system now supports almost all possible order patterns, but the most probable paths are presented at a higher "volume" than those that are less probable.
OK, it turned out to be more than two cents, but the bottom line is this: If you have a chance to visit the environments in which your POS will be used, analyze customer/employee interactions, etc. ...you should take it. Contextual observations and analysis are invaluable in correctly applying heuristics to your situation.
Good luck!
Dr. Kevin Scoresby
FYI - I'd enjoy talking further about this if you or anyone else in the group would like. My office phone number is on my "About Us" page at POSDesigns.com, or you can use the form to initiate an email conversation. Feel free to call anytime during business hours U.S., East Coast Time.
Devstuff already provides some great answers. In addition:
Create a prototype design (can be simply color-printed on paper) and test this in a scenario that is as realistic as possible, i.e. in a store, with a real future user. Enact a few common scenarios and ask the user to really 'use' your prototype as he / she would use the final product. Obtain feedback through interview and observation.
One way to evaluate your design is to check if you have applied the CRAP principles of design. This article discusses how this can relate to user interface design.
In addition to what has already been posted, here are some tips we picked up along the way.
We use two distinct UI's, one for touch-screen with large bold buttons and one for mouse/keyboard entry. the code behind them is the same just the layout is different.
For touch screens
Try not to have pop-up messages that take focus away from the main form, as users may not be looking at the screen, for example if they are chatting with the customer. we found that if this happen users will continues scanning products unaware that they are not been entered into the sale.
If using a bar code scanner be aware that they sometimes send an enter key after the bar code, that will active focused controls (saying yes/no to pop-ups). To help prevent this we disable the enter key-press on buttons, so only a mouse/finger press will fire the click event. we also turn tab stop to false (may be called different in you language), to stop controls that are touch only from getting focus.
As far as colours go we try to stick to bold button and font colours that can easily be distinguished/read in poorly lit rooms and on screens with glare, as most times users are not in the position to move the screen should they have problem reading it.
Anything you can do to speed up/ help the user is a good thing, for example on our payment screen, as well as having 0..9 keys for payment entry, we also have £1,£2,£5,£10 etc so users don't have to add up the money they are given, they can just press the key for each coin/note they received from the customer.
The best tip I can give is to remember that you are designing for a completely different environment form a desktop application, that would be used in an office. and that users may of never used a computer before. since POS systems are usually locked down, try to make it as easy to use out of the box as possible.
another thing to consider is personas (as introduced in cooper's "the inmates are running the asylum").
essentially, you make up a few canonical "users". give them names, hobbies, skills, a picture, and use them as the people you are designing for.
ie:
billy the cashier: has some computer experience (playing on his ps2). he's in high school, may go to community college. he's a primary user of the system, and wants to be able to learn the new system quickly.
cyrus the manager: needs to manage the cashiers. needs a way, with only his authorization, void transactions and be able to review logs of the sales for making reports as well as managing "shrinkage" (theft). he has 2 kids, lives out in the suburbs so has a 45 minute commute; therefore he doesn't want to spend extra time wrangling the system.
you may need three or four personas; any more than that and it becomes hard to design for.
I highly recommend the book "inmates are running the asylum", plus cooper wrote another book: "about face"; which I have yet to read.
good luck!
I would recommend doing some sort of usability survey amongst your current user group. There is no need for this to be a complicated or highly scientific survey. Present them with simple questions to determine:
The users priority when using the system (accuracy of task, speed, aesthetics)
Preferred input devices
Work flow through such a system
Level of education and domain knowledge
I have found that a lot can be learnt from a simple survey like this and can be applied to your UI design to ensure that the users usability experience is satisfactory.
Great comments from everyone else. I'll just add that there's also an article by Dr. Kevin Scoresby titled "How to Design a (POS) System that Everybody Hates" that discusses usability of POS systems and adds a few points to what people have already mentioned, such as:
Don't punish the employee for customer choices
Avoid creating conflicts with the real world
Avoid color coding (1 out of 10 males has a form of color blindness)
I've also discovered lots of helpful POS design tips at POSDesigns.com. One thing I found interesting is that by focusing too much on the number of button presses, you can actually impact speed--which is often a primary goal. There's also a tip titled "Five Factors that Influence Speed" that I found helpful.
Good luck!
Kyle
There are already some really good systems out there i.e. Tabtill for Win 8 http://www.tabtill.com or Shopkeep for iOS http://www.shopkeep.com. The fewest number of clicks your user need to do the better. As I am also involved in coding for such solutions and having worked with clients using various POS systems, some can be really frustrating. Remember watching cashiers in a bar tapping 10 times just to take payment for a couple of items, their fingers are hopelessly hovering over the screen trying to find the right colourful button. Keep it simple! Allow sorting of your visible product range, categorize them or use barcode reader. Keep at least 5% gap between buttons and don't let silly animations slow down your UI. Either invent your own or just copy what is already out there with your own twist.
I'm developing a UI (AJAX-enabled; LAMP server) which will allow a user to designate regions in which a company operates. A "region" in this case may be a state (if dealing with the US) a province (Canada), or entire country (everyone else).
As there are 195 countries in the world, I would like to avoid a multi-select box or list of checkboxes. In the workflow leading to this particular screen, the user will have already entered the full address of the company, so I have a starting region to work from.
Since the majority of companies only operate out of their own region, and those covering multiple regions tend not to branch out too far, I am considering displaying the list of regions gradually based on proximity. I realize at some point (I'm using 3 passes for now) the full list will need to be displayed; I'm just trying to delay the user from reaching that point as it's a definite edge case.
Here is a PNG mockup that explains this concept a bit more clearly. (196kb)
Questions:
What suggestions do you have for the actual form interaction? This has not been presented to representative end users yet, but I'm open to all suggestions during the prototyping stage.
Do you think 'rolling up' US states and/or Canadian provinces between transitions will negatively affect the user's spatial memory?
More clearly: after the 3rd pass, the company will operate in every US state - so convert those 50 inputs into one.
Are there any existing applications that have utilized this approach to use as a baseline or demo?
And, since I know my developer will want to know - what would be the easiest way to store each region's proximity? Lat/long of the center? Lat/long of each corner of a 'bounding box' (more accurate)? I'm assuming we will end up writing some proximity calculations based on the lat/long of the company's actual address.
Are you expecting users to read the map in order to know what list of checkboxes to go to? If your users have than level of geographic ability, then it’s less work for them to select the regions directly from the map, rather than have them make the map-to-Proximity-Level cognitive transfer, followed by a Proximity-Level-to-region transfer.
If some users do not have that level geographic expertise (you may be surprised how many Americans cannot find their own state on a US map), then I’d try, perhaps in addition to the map, no more than two lists, one proximal (the default) with regions close to the home address, and one exhaustive. I can’t see users with weak geographic abilities being be able to handle multiple arbitrary levels of proximity. People who can’t read maps well are not going to able to estimate the proximity level of one region to another. So the idea is to try a proximal list and if that doesn’t work, then forget about proximity and go exhaustive –don’t send your users wandering among proximity levels looking for Idaho (“I swear it’s near Indiana”).
By default, show the proximal list with regions likely to satisfy most of your users based on research of your likely clients. A “more” button displays the exhaustive list. Both lists should be sorted alphabetically, except first subdivide the exhaustive list into States of the US, Provinces & Territories of Canada, and Country (which includes the US (all) and Canada (all)).
You can provide some command buttons to select multiple regions (e.g., “All 48 contiguous US states, All of South America), allowing users to de-select some regions afterward. For this reason, I wouldn’t roll anything up until the user commits the input.
As an example of someone using a map plus list (all in HTML, no less), see http://justaddwater.dk/2007/12/21/map-with-positions-in-css/
I am not really clear what it is that you are trying to achieve from the current UI (are you looking for branch offices? other companies? etc?)
I am not a big fan of using pure geographical proximity to define regions. For example, if one company operates in NYC, it could have an office in NJ which could well be as far as the moon. On the other hand, for a company in anchorage, an office in Vancouver could still be within the region. Unfortunately, state boundaries are fairly meaningless too. For example, I live in western PA, and can tell you that while Pittsburgh and Philly are in the same state, they could be different countries for all that matters, and most companies have offices in each.
If your project is lamp based, why not just let a user click a point on the map, and based on that ask him what he means (e.g., nearest city, entire county, entire state, entire country?. If you then need to define the entire region, you can perhaps use some sort of a grab tool to click or delineate all the other regions that could be part of it?
Either way, present your offices as pushpins on the map, and then maybe have a list on the side the way that standard google maps handles searches.
It may be a lot of work, but if it's an important form, users may prefer that over manual text entry or selections from a list.