Wikimedia Apps/Suggested edits/nl



Welkom bij Voorgestelde bewerkingen
Voorgestelde bewerkingen is een nieuwe manier om Wikipedia te bewerken op Android. We vinden het fijn dat u het probeert.



Wat is Voorgestelde bewerkingen?
Voorgestelde bewerkingen biedt mogelijkheden voor kleine maar essentiële bijdragen aan Wikipedia. We willen meer bekendheid geven aan het feit dat iedereen Wikipedia kan bewerken. Ook willen we het bijdragen voor iedereen makkelijker en toegankelijker maken.



Beginnen met Voorgestelde bewerkingen
De startpagina van Voorgestelde bewerkingen bestaat uit de volgende gebieden: Profielstatistieken/bijdragegeschiedenis en bijdragemogelijkheden. Bijdragemogelijkheden vormen het centrale element van Voorgestelde bewerkingen. Hier kunt u manieren vinden om aan Wikipedia bij te dragen. Momenteel bieden we taken aan om artikelbeschrijvingen en afbeeldingsbijschriften toe te voegen of te vertalen. Als u meer wilt weten of wilt leren bewerken als een professional, bekijk dan de speciale secties hieronder:



Binnenkort voegen we meer soorten bijdragen toe. Houd ons in de gaten.

Profielstatistieken geven informatie weer over uw activiteit binnen Voorgestelde bewerkingen. Ze worden ingevuld zodra u uw eerste voorgestelde bewerkingen heeft gemaakt.

Als u op de kaart tikt, gaat u naar de pagina bijdragegeschiedenis. De bijdragegeschiedenis vermeldt alle typen bijdragen die beschikbaar zijn in Voorgestelde bewerkingen. U kunt filteren op bewerkingstype en zien hoeveel paginaweergaven de artikelen waaraan u heeft bijgedragen in de afgelopen 30 dagen hebben gehad. Als u op een item tikt in de lijst bijdragegeschiedenis, gaat u naar de bewerkingsdetailpagina (overzicht wijzigingen), waar nog meer informatie over de specifieke bewerking wordt weergegeven.
 * Contributions - geeft het aantal van de bijdragen weer die u in de afgelopen 30 dagen heeft gemaakt met Voorgestelde bewerkingen.
 * Pageviews - geeft het totale aantal keren in de afgelopen 30 dagen weer dat anderen items hebben bekeken waaraan u hebt bijgedragen met behulp van Voorgestelde bewerkingen.
 * Edit streak - geeft weer hoeveel dagen u zonder pauze hebt bijgedragen via Voorgestelde bewerkingen. Als u al een tijdje niet hebt bijgedragen, wordt uw laatste bijdragedatum weergegeven.
 * Edit quality - op basis van hoe vaak een van uw bijdragen is teruggedraaid (dat wil zeggen: ongedaan gemaakt door een andere redacteur). Hoe minder bijdragen teruggedraaid worden, hoe beter de bewerkingskwaliteit.



Artikelbeschrijvingen




Wat zijn artikelbeschrijvingen?

 * Korte, meertalige beschrijvingen van items (bv. Wikipedia-artikelen)
 * Artikelbeschrijvingen zijn geen volledige zinnen, maar kleine stukjes informatie.
 * In de meeste gevallen is de juiste lengte tussen twee en twaalf woorden.



Waar worden artikelbeschrijvingen voor gebruikt?
Artikelbeschrijvingen worden weergegeven in de apps onder Wikipedia-artikeltitels om lezers te helpen het artikel te vinden waarnaar ze op zoek zijn. Artikelbeschrijvingen worden opgeslagen en onderhouden op Wikidata en zijn ontworpen om items met dezelfde of vergelijkbare labels ondubbelzinnig te maken. Beschrijvingen worden ook buiten de Wikipedia-site en apps getoond, bijvoorbeeld in Google-zoekopdrachten.

Artikelbeschrijvingen vatten een artikel samen om lezers te helpen het onderwerp in één oogopslag te begrijpen. Deze staan in de Wikimedia-gemeenschap bekend als Wikidata-beschrijvingen.



Tips voor het maken van artikelbeschrijvingen
Article descriptions should ideally fit on one line, and be between two to twelve words long. They are not capitalized unless the first word is a proper noun, and do not normally begin with initial articles (a, an, the). For example:


 * painting by Leonardo da Vinci (title description for an article about the Mona Lisa)
 * Earth’s highest mountain (title description for an article about Mount Everest)

Other tips for writing good article descriptions:

(e.g., ‘current Prime Minister of…’) (e.g., ‘the best…’)
 * Avoid information that is likely to change
 * Avoid opinionated, biased or promotional wording
 * Avoid controversial claims

More information is available on the Wikidata descriptions help page.

More on article descriptions
Article descriptions are stored and maintained on Wikidata, a project of the Wikimedia Foundation which provides a free, collaborative, multilingual, secondary database supporting Wikipedia and other projects.


 * About Wikidata
 * Wikidata help page about article descriptions
 * Guidelines for writing article descriptions in English
 * Guidelines for writing short descriptions on English Wikipedia

What are image captions?

 * Short, multilingual descriptions of image files
 * Limited to 250 characters in length and cannot contain markup

What are image captions used for?
Image captions describe an image to help readers understand the meaning and context of an image. They are also used to provide alternative information for an image if people cannot view it, e.g. because of a slow internet connection or if people use a screen reader.

Tips for creating image captions
Image captions should be short descriptions of what the image shows. They are generally four to twelve words long. They can also contain information about the artist or creator of the image.

Remember to keep your captions neutral. Avoid making value judgements such as "beautiful", "good" or "ugly".

The difference between the image description and the image caption is that the description can have a lot of information about the file. If the image is a scan it can have details about the original photograph or artwork. It can have links. The image caption should ignore all this and just describe what it shows, not the information about the file.

A good image caption should:


 * Aim to briefly describe the contents of an image
 * Describe the image such that those with vision or other impairments can imagine what it looks like
 * Contain some keywords that people are likely to use to search for an image (so a picture of a cat should include the word "cat" somewhere in the caption)

In many cases, the caption will be similar or identical to the description (or even the file title!). For example, File:Fire station Hallstatt - October 2017 - 02.jpg has the English caption "Hallstatt fire station in October 2017".

More on image captions
Image captions are stored and maintained on Wikimedia Commons, a project of the Wikimedia Foundation which provides an online repository of free-use images, sounds, other media, and JSON files supporting Wikipedia and other projects.

Image tags

 *  See also: Commons:Depicts 

What are image tags?
"Image tags" is a shorthand phrase for what the Commons community calls Depicts statements.

What are image tags used for?
By adding image tags, you will help make images easier to search for on Commons, the free license image repository that Wikipedia uses for images in its articles.

Tips for adding image tags
Please add tags conservatively. If there are multiple items clearly and deliberately depicted by the image, all should be added as separate tags, within reason. For example, should be tagged with "Bonnie and Clyde", "Bonnie Parker", and "Clyde Barrow". Identify the most important thing(s) in the image.

Be as specific as you can. Search for the most relevant tags by tapping "+ Add tag". You may see a number of search results, but resist the urge to add a large number of semi-relevant tags. In the example shown below, the picture is of the Williamsburg Bridge, but that tag has not been added. Add it yourself by tapping "+ Add tag" and searching for "Williamsburg Bridge".

Where is the train algorithm task?
Due to the train image algorithm task serving as a MVP for the Android team to learn from and build the full image matching feature, the train image algorithm MVP has been sunset. With the help of Wikipedians like you, we have improved the algorithm and have enough learnings to proceed with the next phase of our work to build the full image matching feature. Our lessons from the experiment will be available on the Add an Image project page. You can watch participate in the next phase of this work at Growth team's project page.

What is the train algorithm task?
Wikipedia articles are written and edited by thousands of volunteers from around the world. Unfortunately, many articles lack images. The Train Algorithm task is a type of Suggested Edits task that will show logged-in Android users articles and images along with its associated information, so that users can determine if the image is a good illustration of the contents of the article displayed.

The images will be suggested to you using an algorithm. The algorithm will pull images from other sources and suggest a match with an article that does not have an image.

Unlike other Suggested Edits tasks, the Train Algorithm task will not save any edits to any Wiki projects and is a temporary task. The purpose of the Train Algorithm task is to gather data, improve our image matching algorithm, and inform our design for future releases of an image matching task on Android and Mobile Web.



Tips for training the image algorithm
To best determine if an image is the right match for an article you should review:
 * Image (zoom in to review more details)
 * Image file name
 * Image description
 * Image suggestion reason
 * Article content

Dialog options
In the task you can select Yes, No or Not Sure, to the question of if you would add the image to an article.


 * Yes indicates the image is a good illustration to help readers understand the topic of the Wikipedia article
 * No indicates the image would not help readers understand the topic of the Wikipedia article. Reasons the image would not help be a good fit for the article includes:
 * Not Relevant, which indicates the image depicts a topic that is not associated with the article that is being shown
 * Not enough Information, which indicates the metadata shared with the image does not provide enough details for you to confidently indicate the image would help readers better understand the article
 * Offensive, which indicates the image is inappropriate
 * Low Quality, which indicates you can not see the image well enough to confidently say it is a good illustration of the article being shown and help readers understand the topic
 * Don't know this subject, which indicates you do not feel you have the needed expertise to determine if the image would help readers understand the topic of the Wikipedia article
 * Cannot read the language, which indicates the words written in the image, or the metadata is in a language you do not understand, and are then unable to confidently say the image would help readers understand the topic of the Wikipedia article
 * Other, which indicates there is another reason the image is not a good match for the article
 * Not Sure indicates you are not certain whether or not the image would help readers understand the topic of the Wikipedia article. Reasons for not being sure could include:
 * Not enough Information, which indicates the metadata shared with the image does not provide enough details for you to confidently indicate the image would help readers better understand the article
 * Cannot see image, which indicates you can not see the image well enough to confidently say it is a good illustration of the article being shown and help readers understand the topic
 * Don't know this subject, which indicates you do not feel you have the needed expertise to determine if the image would help readers understand the topic of the Wikipedia article
 * Don't understand the task, which indicates you do not understand the Train Image Algorithm task
 * Cannot read the language, which indicates the words written in the image, or the metadata is in a language you do not understand, and are then unable to confidently say the image would help readers understand the topic of the Wikipedia article
 * Other, which indicates there is another reason you are not sure if the image would be a good match for the article

Daily goal
The 'Train image algorithm' task consists of a daily goal. To reach the daily goal, you need to evaluate 10 image suggestions. The goal resets to 0 on the next day. You can always evaluate more than 10 image suggestions per day, this should just serve as an indicator of your daily progress.

When will you roll out the full image matching task?
The Android and Growth teams will collaboratively evaluate the outcomes of this MVP, and determine next steps for a task that places images in articles in July 2021. During that time, the teams will update the MVP project page with our findings and share when we will offer the image matching task.

How can I follow the outcome of this MVP when it ends?
You can watch our Add an Image MVP project page for updates about this effort. We would also value your feedback on our talk page.