I am trying to develop an ASP.net MVC website in which I need to show a map (whole world) with several markers and additional information for every marker.
Does anyone know a good library that would support that and which (if possible) also lets me use "offline" maps stored on my own server (open street maps for example).
It will be an intranet application which means in case of google/bing yearly license costs would have to be paid. The customer doesn't want that, but in general the library can be commercial (one-time per server and/or developer fee).
I already had a look at "ThinkGeo Map Suite", any other suggestions or recommendations.
SharpMap, it's flexible and easy to implement, can use with shapes or from spacial db.
for details... http://sharpmap.codeplex.com/
there is a couple examples who does exactly what you need, so can start from these
exist other libraries but I don't try it, research for another options.
Answer
Manifold is a very cheap system which has an basic internet map server framework:
http://www.manifold.net/info/ims.shtml
You already suggested ThinkGeo, I would put it in the same basket as Manifold. Be sure to evaluate performance and limitations with both packages.
Discussion
You'd be hard pressed to find a pure NET library for mapping that works well and won't blow out your budget (see ESRI). Depending on your skill level and your knowledge of GIS systems, I would suggest creating your own web map server and just embed it in your web application.
Some good environments for this which I can recommend are:
MapServer
GeoServer
As far as displaying and interacting with the map, there are several web based platforms available:
GIS SDKs For Web Apps
Related
I have been reading the abstracts on the website http://www.rikulo.org but all those cryptic vague statements do not help me. The examples are all about visuals.
I do not understand what this framework is capeable of doing. The big picture is missing.
What kind of apps can i build with rikulo?
Is there any access to the hardware?
Can is use the smartphones sensordata and send e.g. coordinates from my smartphone to a web service?
What are the limitations?
As described in this blog, Rikulo is aimed to provide a structured UI model for Web and mobile programming. We are the same team who developed ZK. With Rikulo, we'd like to take a step further since many things have been changed since we developed ZK in 2005. Also, both Dart and HTML 5 are young. It is an excellent moment to explore the best possible UI architecture for both Web and mobile programming.
For example, we use absolute positioning to give programmers 100% control the layout of UI rather than spending hours to figure out why it fails in certain combination. Another example is "recursive layered structure", such as layout manager and visual effect handling -- rather than ad hoc features targeting specific problems individually.
On the other hand, we don't have many widgets yet. It might be the reason that confused you. As a Apache licensed project, we hope we can have an active community for building widgets and addons, as long as we can really provide a solid and elegant architecture -- it is what we focus now and keep refining.
To access the hardware, you can use Rikulo Gap which is based on Cordova/PhoneGap. To communicate back the server, you can use Web socket or HttpRequest. We will have more advanced support for jsonizing, caching and communicating Dart objects between client and server, but it is not ready yet.
Technically, there is no limitation. Of course, the current number of widgets is definitely not enough, but it will get more in the near future. Furthermore, you always can create them with HTML 5 (and contribute back). However, for mobile applications, one thing you have to keep in mind: the performance won't be as good as the apps written in Objective C. The good is Rikulo is cross platform and your app can be accessed with Web browsers and as a native app.
I am beginning work on an individual project to bring an existing product out of the dark ages of classic ASP and into the light. My biggest decision to make before embarking on this lengthy journey is determining what frameworks and methodology I will implement for the new design.
Right now I am looking at MVC or MVVM (from what I gather this is just Silverlight?) for the web interface, Entity Framework or something I write myself as the model and MSSQL as the data.
Unfortunately I am just a fledgling programmer and I am not particularly aware of trends in the world of programming in general. I don't know what is just a passing fad and what technologies actually have lasting potential. I would really like to use something that is likely to remain relevant for some time. So I am looking to the professionals here for input on ideas that worked for you, pitfalls to watch out for and things to keep an eye on.
I appreciate any and all suggestions, keeping in mind that using the Microsoft and .Net is something of a prerequisite. I really want to make sure I am headed in the right direction before I start as this will probably take several months.
As for frameworks I personally suggest:
ASP.NET MVC 3 of MVC 4, depending on the question if beta software is allowed.
Entity Framework 4.3 or 5.0. 5.0 is a lot faster (is has auto compilation) but it's still a Release Candidate.
AutoMapper to map between Entities and ViewModels.
Ninject for dependency injection (useful if you want to write unit tests).
JQuery for stuff like clientside validation (integrates perfectly with ASP.NET MVC).
Possible some CSS framework like Bootstrap.
Maybe RestSharp so you can easily perform requests.
In case it's a cloud service (most SaaS are) and you'd like to host it on Azure (brilliant integration with the .NET stack) you'll need the Azure SDK.
As for software achitecture:
Use service layers
Use the repository patterns
Use ViewModels to pass to your view instead of entities
Set up a dependency injection container
That's my advice, I personally find this a golden combination for building enterprise applications (while not wasting too much time configuring lots of things).
Pitfalls:
I don't know if unit testing is really necessary. I should definately keep it in mind while setting up the architecture, but I personally choose to do that later because I don't even know if my product will succeed, so I can better put my time in building a fast Minimal Viable Product.
Don't assume anything. You can waste months of your precious time working on a cool feature that you think everyone will like, but often this is not the case. Do just the absolutely required minimum, and improve it later if your users like it.
I will add more to #Leon suggestions as I see those suggestion are great from application framework perspective, while I wanted to write here from cloud methodology perspective.
As you have chosen SaaS, definitely you are moving completely in Cloud while bring your application and data to cloud all together, that's great!!
There are several layers to any cloud application and to understand lets see what a cloud service stack look like. If we take an example of Windows Azure:
You have Compute, where your application runs with a web server (or not).
You have Azure table store which you can use to store key value pair in a row and then access them very fast.
You have Azure Queue allows decoupling of different parts of a cloud application, enabling cloud applications to be easily built with different technologies and easily scale with traffic needs.
You have Access Control Services to authenticate users through OpenID or AD
You have service bus to connect other services in cloud or on-premise at 3rd party.
You have Azure Blob storage to use as web based flat file server
You have Azure Cache (an in-memory cache build to scale in cloud)
You have SQL Azure as you cloud database
There are many more services which you can explorer and use
So when you decide to move your application from traditional web hosting to cloud you really have to look about how to take advantage of these different cloud services to scale your application when needed and save you lots of money.
With you application in Cloud you try something as below:
Keep you application logic as small as possible
Keep your static content outside the compute
Use cloud based cache for fast access as application scale out
Move data out of traditional RDBMS databases to NoSQL Framework (key-value pair, document etc to save money and flexibility), if possible and applicable
Take advantage of other available services to reduce application complexity
If you consider above aspect in your mind you will create a true cloud based application which will be fast and will save you money.
We are building an image and file hosting website and we will save these files on our servers, so I want to know if there are any best practices or standards I need to read and follow to make our website scalable and easy to extend in the future.
Is there a book or articles or videos talking about this subject, please share.
As per my experience to deal with large data.
its always best to opt for Cloud, check for "Amazon S3" (Amazon AWS) or Windows Azure.
features like "CDN" (cloud front) is a big plus.
I believe this is not a simple question that can be answered without knowing
how many files are expected ?
how many users/files accesses per hour/day/minute ?
your usage scenarios with this files (downloading? streaming? how many concurrent files downloaded at once?
are you stuck in one particular OS (windows) and filesystem (NTFS), or is there freedom in this ?
My personal note : Building own image/file hosting is not a trivial task, i strongly recommend you to hire somebody with experience from this area.
I would recommend that if possible, you look at a 3rd party solution that provides an api. you'll then get the benefits of lower cost of ownership, no maintenance costs for the hardware and continual updates thrown in for free when the 3rd party adds new features to the core offering. I know this from 1st hand experience as we scoped out the options for doing this in a recent project and came to the conclusion that we'd spend 100 times more on our own solution and even then, may not get it right. We opted for a company called Razuna who offer both a hosted and open source version of their platform. Their api is very straightfwd and can be consumed inside your mvc app with potentially only a few days effort (depending on your use case). The beauty of this approach is that the hosted elements are actually on the nirvanix backbone and are served via their CDN - so win win.
You can get the details at:
http://www.razuna.com
and can view the api docs at:
http://wiki.razuna.com/display/ecp/Developer+Guides
Good luck and if you need any further real-life guidence on this, feel free to come back. Oh and btw, we were also able to ask for 'paid for' features to be added to the core offering at pretty much standard market day rates.
A recent announcement by Google about the Google Prediction API sounded very interesting. It could be useful for a project that is coming up, and would probably do a better job than some custom code I was considering.
However, there is some vendor lock-in. Google retain the trained model, and could later choose to overcharge me for it. It occurred to me that there are probably open-source equivalents, if I was willing to host the training myself (I am) and live without their ability to throw hardware at the problem at a moment's notice.
Last time I looked at 3rd Party computer training code was many years ago, and there were a lot of details that needed to be carefully considered and customised for your project. Google appear to have hidden those decisions, and take care of them for you. To me, this is still indistinguishable from magic, but I would like to hear whether others can do the same.
So my question is:
What alternatives to Google Prediction API exist which:
categorise data with supervised machine learning,
can be easily configured (or don't need configuration) for different kinds and scales of data-sets?
are open-source and self-hosted (or at the very least, provide you with a royalty free use of your model, without a dependence on a third party)
Maybe Apache Mahout?
PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
Have been looking recently at tools like google prediction API, one of the first ones I got put on to was Weka machine learning tool which could be worth checking out for anyone looking.
I'm not sure if it's relevant, but directededge seams to be doing exactly that :)
There is good free for use service Yandex Predictor with 100000/day request quota. It works for text only, supports several languages and spell correction.
You need to get free API Key, then you can use simple RESTful API. Api support JSON, XML and JSONP as output.
Unfortunately I cannot find documentation in English. You can use Google Translate.
I can translate docs if there is some demand.
Which of the two provides a better API for developing on top of?
Although there is a virtual Google Search Appliance available for download, no such equivalent is present for FAST.
So looking to developers with experience in either of these products to give suggestions and links to documentation. (especially for FAST as there's none available on their site)
Kind regards,
I'm pretty sure that FAST does not provide a trial download of their Enteprise Search Platform (ESP) today nor it's SDK (which is useless without ESP).
FAST is pretty much the industry leader for customization (Google is popular as simple out of the box solution and Autonomy seems to be the leader in compliance) which is what you are likely intrested in an API for. But not Cheap. Internal Python customization for processing documents, exteral .NET & Java API for interacting with the service.
Also, you if you are looking for a basic Enteprise Search + API, google on "Solr" project.
I think FAST provides a free trail version. Along with it comes the API documentation and other manuals. My company uses it. I use it.
Answering your queston, FAST is obviously better than Google search appliance (for various reasons). That's my view.
Freddie
I have worked on Google Search Appliance and it works great.
I can search in meta-data, get selective data back from query, see real time status of documents that are getting crawled, scalable with GSA6.14 and all great support from Google.
Apache Solr is a great solution with a very flexible client API. You should definitely check it out. We are moving from FAST to Solr currently & I find the features and API of Solr much better than FAST ESP.