Re: [Wikidata] Wikiopinion - Structured opinions

[Quico Prol]

Hi Kingsley

To make the connection of your review with the corresponding wikidata item,
 you first have to create the item for this song in wikidata, so:

1) Go to https://www.wikidata.org/
2) Press "Create a new item" in left sidebar under wikidata logo
3) Enter "Label" = "Charity" and description , it could be something like
"GLITCH56 song"
4) Press "Create" button
5) Start adding "Statements". You can follow as an example a similar item
like  this song https://www.wikidata.org/wiki/Q380825
6) Add the statement for the review:  "lib.reviews
ID" = ac478596-e571-4891-b882-5508aea9d9bf

greetings

2017-01-23 13:29 GMT+01:00 Kingsley Idehen :

> On 1/21/17 12:42 PM, Quico Prol wrote:
>
> Maybe you would like to take a look to https://lib.reviews a wiki for
> reviewing all kind of things using wikidata items
>
>
> Given the document at: https://lib.reviews/review/ac478596-e571-4891-b882-
> 5508aea9d9bf
>
> How do I make the connection with what you state above re. wikidata items?
>
> Kingsley
>
>
> 2017-01-05 20:39 GMT+01:00 Hector Perez :
>
>> Kingsley, thanks for sending it to DBpedia's list too.
>>
>> I'll have a look at your Linked Data Middleware!
>>
>> On Wed, Jan 4, 2017 at 8:36 PM, Kingsley Idehen 
>> wrote:
>>
>>> On 1/4/17 3:34 AM, Hector Perez wrote:
>>>
>>>
>>> To sum up, we think that a social network that challenges what you post
>>> and organises who agrees on what and why would complement Wikipedia and the
>>> traditional story telling. What do you think? Would you like to join us?
>>> Should this project be non-profit or for-profit? Would you donate or help
>>> us to fund raise?
>>>
>>> Kind regards,
>>>
>>> Hector
>>>
>>> [1]. Original post: https://medium.com/@HectorPere
>>> z/wikipedias-social-network-578b0257b8ae
>>>
>>>
>>> Nice idea! I've copied in the DBpedia list, as this would be of interest
>>> to that community also.
>>>
>>> I passed your Medium post through our Linked Data Middleware service en
>>> route to demonstrating what might complement your ultimate goal. Here are
>>> the results:
>>>
>>> [1] http://linkeddata.uriburner.com/about/html/https/medium.com/
>>> @HectorPerez/wikipedias-social-network-578b0257b8ae#.bvs2iko2w
>>>
>>> [2] http://linkeddata.uriburner.com/describe/?url=http%3A%2F%2Fl
>>> inkeddata.uriburner.com%2Fabout%2Fid%2Fentity%2Fhttps%2Fmedi
>>> um.com%2F@HectorPerez%2Fwikipedias-social-network-578b0257b8
>>> ae=1
>>>
>>> Fundamentally, what you see is the effect of loosely-coupled NLP, AI,
>>> and Machine Learning oriented services that collectively contribute to a
>>> final Linked Open Data graph that represents a variety of entity
>>> relationships and entity relationship types :)
>>>
>>>
>>> --
>>> Regards,
>>>
>>> Kingsley Idehen 
>>> Founder & CEO
>>> OpenLink Software   (Home Page: http://www.openlinksw.com)
>>>
>>> Weblogs (Blogs):
>>> Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
>>> Blogspot Blog: http://kidehen.blogspot.com
>>> Medium Blog: https://medium.com/@kidehen
>>>
>>> Profile Pages:
>>> Pinterest: https://www.pinterest.com/kidehen/
>>> Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen
>>> Twitter: https://twitter.com/kidehen
>>> Google+: https://plus.google.com/+KingsleyIdehen/about
>>> LinkedIn: http://www.linkedin.com/in/kidehen
>>>
>>> Web Identities (WebID):
>>> Personal: http://kingsley.idehen.net/dataspace/person/kidehen#this
>>> : 
>>> http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this
>>>
>>> ___ Wikidata mailing list
>>> Wikidata@lists.wikimedia.org https://lists.wikimedia.org/ma
>>> ilman/listinfo/wikidata
>>
>> ___ Wikidata mailing list
>> Wikidata@lists.wikimedia.org https://lists.wikimedia.org/ma
>> ilman/listinfo/wikidata
>
> ___
> Wikidata mailing 
> listWikidata@lists.wikimedia.orghttps://lists.wikimedia.org/mailman/listinfo/wikidata
>
> --
> Regards,
>
> Kingsley Idehen   
> Founder & CEO
> OpenLink Software   (Home Page: http://www.openlinksw.com)
>
> Weblogs (Blogs):
> Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
> Blogspot Blog: http://kidehen.blogspot.com
> Medium Blog: https://medium.com/@kidehen
>
> Profile Pages:
> Pinterest: https://www.pinterest.com/kidehen/
> Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen
> Twitter: https://twitter.com/kidehen
> Google+: https://plus.google.com/+KingsleyIdehen/about
> LinkedIn: http://www.linkedin.com/in/kidehen
>
> Web Identities (WebID):
> Personal: http://kingsley.idehen.net/dataspace/person/kidehen#this
> : 
> http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this
>
>
> ___
> Wikidata mailing list
> Wikidata@lists.wikimedia.org
> https://lists.wikimedia.org/mailman/listinfo/wikidata
>
>

Re: [Wikidata] Wikiopinion - Structured opinions

[Kingsley Idehen]

On 1/21/17 12:42 PM, Quico Prol wrote:
> Maybe you would like to take a look to https://lib.reviews a wiki for
> reviewing all kind of things using wikidata items

Given the document at:
https://lib.reviews/review/ac478596-e571-4891-b882-5508aea9d9bf

How do I make the connection with what you state above re. wikidata items?

Kingsley
>
> 2017-01-05 20:39 GMT+01:00 Hector Perez  >:
>
> Kingsley, thanks for sending it to DBpedia's list too.
>
> I'll have a look at your Linked Data Middleware!
>
> On Wed, Jan 4, 2017 at 8:36 PM, Kingsley Idehen
> > wrote:
>
> On 1/4/17 3:34 AM, Hector Perez wrote:
>>
>> To sum up, we think that a social network that challenges
>> what you post and organises who agrees on what and why would
>> complement Wikipedia and the traditional story telling. What
>> do you think? Would you like to join us? Should this project
>> be non-profit or for-profit? Would you donate or help us to
>> fund raise?
>>
>> Kind regards,
>>
>> Hector
>>
>> [1]. Original post:
>> 
>> https://medium.com/@HectorPerez/wikipedias-social-network-578b0257b8ae
>> 
>> 
>
> Nice idea! I've copied in the DBpedia list, as this would be
> of interest to that community also.
>
> I passed your Medium post through our Linked Data Middleware
> service en route to demonstrating what might complement your
> ultimate goal. Here are the results:
>
> [1]
> 
> http://linkeddata.uriburner.com/about/html/https/medium.com/@HectorPerez/wikipedias-social-network-578b0257b8ae#.bvs2iko2w
> 
> 
>
> [2]
> 
> http://linkeddata.uriburner.com/describe/?url=http%3A%2F%2Flinkeddata.uriburner.com%2Fabout%2Fid%2Fentity%2Fhttps%2Fmedium.com%2F@HectorPerez%2Fwikipedias-social-network-578b0257b8ae=1
> 
> 
>
> Fundamentally, what you see is the effect of loosely-coupled
> NLP, AI, and Machine Learning oriented services that
> collectively contribute to a final Linked Open Data graph that
> represents a variety of entity relationships and entity
> relationship types :)
>
>
> -- 
> Regards,
>
> Kingsley Idehen 
> Founder & CEO 
> OpenLink Software   (Home Page: http://www.openlinksw.com)
>
> Weblogs (Blogs):
> Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
> 
> Blogspot Blog: http://kidehen.blogspot.com
> Medium Blog: https://medium.com/@kidehen
>
> Profile Pages:
> Pinterest: https://www.pinterest.com/kidehen/
> 
> Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen
> 
> Twitter: https://twitter.com/kidehen
> Google+: https://plus.google.com/+KingsleyIdehen/about
> 
> LinkedIn: http://www.linkedin.com/in/kidehen
> 
>
> Web Identities (WebID):
> Personal: http://kingsley.idehen.net/dataspace/person/kidehen#this
> 
> : 
> http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this
> 
> 
>
> ___ Wikidata
> mailing list Wikidata@lists.wikimedia.org
> 
> https://lists.wikimedia.org/mailman/listinfo/wikidata
>  
>
> ___ Wikidata mailing
> list Wikidata@lists.wikimedia.org
> 
> https://lists.wikimedia.org/mailman/listinfo/wikidata
>  
>
> ___
> Wikidata mailing list
> Wikidata@lists.wikimedia.org
> https://lists.wikimedia.org/mailman/listinfo/wikidata

-- 
Regards,

Kingsley Idehen   
Founder & CEO 
OpenLink Software   (Home Page: http://www.openlinksw.com)

Weblogs (Blogs):
Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
Blogspot Blog: 

Re: [Wikidata] Wikiopinion - Structured opinions

[Hector Perez]

Kingsley, thanks for sending it to DBpedia's list too.

I'll have a look at your Linked Data Middleware!

On Wed, Jan 4, 2017 at 8:36 PM, Kingsley Idehen 
wrote:

> On 1/4/17 3:34 AM, Hector Perez wrote:
>
>
> To sum up, we think that a social network that challenges what you post
> and organises who agrees on what and why would complement Wikipedia and the
> traditional story telling. What do you think? Would you like to join us?
> Should this project be non-profit or for-profit? Would you donate or help
> us to fund raise?
>
> Kind regards,
>
> Hector
>
> [1]. Original post: https://medium.com/@HectorPere
> z/wikipedias-social-network-578b0257b8ae
>
>
> Nice idea! I've copied in the DBpedia list, as this would be of interest
> to that community also.
>
> I passed your Medium post through our Linked Data Middleware service en
> route to demonstrating what might complement your ultimate goal. Here are
> the results:
>
> [1] http://linkeddata.uriburner.com/about/html/https/medium.
> com/@HectorPerez/wikipedias-social-network-578b0257b8ae#.bvs2iko2w
>
> [2] http://linkeddata.uriburner.com/describe/?url=http%3A%2F%
> 2Flinkeddata.uriburner.com%2Fabout%2Fid%2Fentity%2Fhttps%
> 2Fmedium.com%2F@HectorPerez%2Fwikipedias-social-network-
> 578b0257b8ae=1
>
> Fundamentally, what you see is the effect of loosely-coupled NLP, AI, and
> Machine Learning oriented services that collectively contribute to a final
> Linked Open Data graph that represents a variety of entity relationships
> and entity relationship types :)
>
>
> --
> Regards,
>
> Kingsley Idehen   
> Founder & CEO
> OpenLink Software   (Home Page: http://www.openlinksw.com)
>
> Weblogs (Blogs):
> Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
> Blogspot Blog: http://kidehen.blogspot.com
> Medium Blog: https://medium.com/@kidehen
>
> Profile Pages:
> Pinterest: https://www.pinterest.com/kidehen/
> Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen
> Twitter: https://twitter.com/kidehen
> Google+: https://plus.google.com/+KingsleyIdehen/about
> LinkedIn: http://www.linkedin.com/in/kidehen
>
> Web Identities (WebID):
> Personal: http://kingsley.idehen.net/dataspace/person/kidehen#this
> : 
> http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this
>
>
> ___
> Wikidata mailing list
> Wikidata@lists.wikimedia.org
> https://lists.wikimedia.org/mailman/listinfo/wikidata
>
>
___
Wikidata mailing list
Wikidata@lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/wikidata

Re: [Wikidata] Wikiopinion - Structured opinions

[Kingsley Idehen]

On 1/4/17 3:34 AM, Hector Perez wrote:
>
> To sum up, we think that a social network that challenges what you
> post and organises who agrees on what and why would complement
> Wikipedia and the traditional story telling. What do you think? Would
> you like to join us? Should this project be non-profit or for-profit?
> Would you donate or help us to fund raise?
>
> Kind regards,
>
> Hector
>
> [1]. Original post:
> https://medium.com/@HectorPerez/wikipedias-social-network-578b0257b8ae
> 

Nice idea! I've copied in the DBpedia list, as this would be of interest
to that community also.

I passed your Medium post through our Linked Data Middleware service en
route to demonstrating what might complement your ultimate goal. Here
are the results:

[1]
http://linkeddata.uriburner.com/about/html/https/medium.com/@HectorPerez/wikipedias-social-network-578b0257b8ae#.bvs2iko2w

[2]
http://linkeddata.uriburner.com/describe/?url=http%3A%2F%2Flinkeddata.uriburner.com%2Fabout%2Fid%2Fentity%2Fhttps%2Fmedium.com%2F@HectorPerez%2Fwikipedias-social-network-578b0257b8ae=1

Fundamentally, what you see is the effect of loosely-coupled NLP, AI,
and Machine Learning oriented services that collectively contribute to a
final Linked Open Data graph that represents a variety of entity
relationships and entity relationship types :)


-- 
Regards,

Kingsley Idehen   
Founder & CEO 
OpenLink Software   (Home Page: http://www.openlinksw.com)

Weblogs (Blogs):
Legacy Blog: http://www.openlinksw.com/blog/~kidehen/
Blogspot Blog: http://kidehen.blogspot.com
Medium Blog: https://medium.com/@kidehen

Profile Pages:
Pinterest: https://www.pinterest.com/kidehen/
Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen
Twitter: https://twitter.com/kidehen
Google+: https://plus.google.com/+KingsleyIdehen/about
LinkedIn: http://www.linkedin.com/in/kidehen

Web Identities (WebID):
Personal: http://kingsley.idehen.net/dataspace/person/kidehen#this
: 
http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this



smime.p7s
Description: S/MIME Cryptographic Signature
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Wikidata mailing list
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Re: [Wikidata] Wikiopinion - Structured opinions

[Hector Perez]

Hi Amit,

Thanks for your email. I'll contact you privately.

Kind regards,
Hector

On Jan 4, 2017 9:44 AM, "AMIT KUMAR JAISWAL" 
wrote:

> Hello Hector,
>
> This all sounds very exciting. Kudos to you!!
>
> According to my own opinion, I would say Wikiopinion.org fall under a
> non-profit project under Wikimedia Foundation.
> Yes, I'm up for this and would like to join as a
> volunteer(Developer/Community Liaison).
> I'll help Wikiopinion.org to fund raise.
>
> Looking forward to join your team.
>
> Regards,
> Amit Kumar Jaiswal
>
> On 1/4/17, Hector Perez  wrote:
> > Hi all, I proposed to create Wikiopinion.org based on our work on
> AgreeList
> > that might fit into Wikidata [1]. I paste it here:
> >
> > Storytelling was the most important way to share knowledge for thousands
> of
> > years — before writing was invented — so our brains evolved to be
> > influenced by stories. As Conor Neil explains, many times we are still
> > “more easily persuaded by one clear and concrete anecdote than by data
> and
> > expert statistical analysis”. He says that, “an anecdote is a one off. It
> > is not data. It is not science. It is dangerous”.
> >
> > This made me think about two things:
> >
> > Firstly, people such as Lydia Pintscher of Wikidata and Dario Taraborelli
> > of Wikicite are working on projects that improve considerably the quality
> > of Wikipedia and they could even accelerate world’s research.
> >
> > Wikidata is a collaboratively edited knowledge base:
> > ...
> >
> > And Wikicite is building a repository of all Wikimedia citations and
> > bibliographic metadata. The sum of all citations:
> > ...
> >
> > Secondly, it also made me think about how this relates to the work we
> have
> > been doing with AgreeList.com With AgreeList, we are creating a ‘platform
> > for informed opinions’ that gathers the opinions of leading experts and
> > influencers and favors the building of rational opinions on issues of key
> > importance. Our first issue was ‘Brexit’ where we collected the opinions
> of
> > almost 2000 opinion-makers on the impact of Brexit to the UK economy,
> > immigration, politics, and education, and built a summary of opinions on
> > both sides to inform the public during the referendum. In other words, we
> > believe in the value of informed opinions over anecdotes and the data of
> > who agrees on what and why can help us to build our own opinion. E.g. if
> > NASA, the Royal Society, Obama, the Pope and a friend of mine who knows
> > more about climate change than me think that it’s real and we should do
> > more to tackle it, I believe it.
> >
> > Similarly, if I read something health-related, I can check the number of
> > doctors who agree or disagree as fast as I see the number of likes on
> > Facebook. If it is more than 95%, I believe it straight away. Done. I
> > learned a new thing today. This way we could fight the fact that false
> > health content seems to be more popular on social media and we could get
> > informed of more topics than ever.
> >
> > When we are interested in a topic and have time, we read about it and
> > contrast different points of views. But when we don’t have time or are
> not
> > interested in something, we believe what our culture, friends and
> > influencers say. And we are so bombarded with information nowadays that
> we
> > can’t get informed about everything all the time.
> >
> > However, when we want to have an educated opinion about a complex topic
> > such as Universal Basic Income, we can read the arguments and even go to
> > the sources where we can find more information. We are still building up
> > the database on Basic Income and it is currently biased towards opinions
> in
> > favour given that it is easier to find them given how early stage the
> > public debate and the AgreeList tool are, but you can see below what
> > different opinion-makers say about Universal Basic Income via Agreelist:
> > ...
> >
> > And when there are many opinions, such as on Brexit, we organise them in
> a
> > board or summary that aggregates the arguments per categories.
> >
> > We can also filter them by profession, university, awards (e.g. Nobel
> Prize
> > winners), etc. E.g:
> > ...
> >
> > How did we get this data? First, the data from occupations comes from
> > Wikidata. Second, the data of who agrees on topics such as these ones is
> on
> > AgreeList. These lists are crowdsourced — people add influencer’s
> opinions.
> > Users only need to provide a source, for example an article in the New
> York
> > Times or the tweet of the person. Moreover, users of the site can vote
> and
> > add their own opinions and, at some point, we could aggregate opinions
> > automatically by semantic analysis. This way we might organise all the
> > opinions in the world on key topics or statements. AgreeList or
> Wikiopinion
> > could one day become ‘The sum of all opinions’.
> >
> > We can also play with Google BigQuery to do joins 

Re: [Wikidata] Wikiopinion - Structured opinions

[AMIT KUMAR JAISWAL]

Hello Hector,

This all sounds very exciting. Kudos to you!!

According to my own opinion, I would say Wikiopinion.org fall under a
non-profit project under Wikimedia Foundation.
Yes, I'm up for this and would like to join as a
volunteer(Developer/Community Liaison).
I'll help Wikiopinion.org to fund raise.

Looking forward to join your team.

Regards,
Amit Kumar Jaiswal

On 1/4/17, Hector Perez  wrote:
> Hi all, I proposed to create Wikiopinion.org based on our work on AgreeList
> that might fit into Wikidata [1]. I paste it here:
>
> Storytelling was the most important way to share knowledge for thousands of
> years — before writing was invented — so our brains evolved to be
> influenced by stories. As Conor Neil explains, many times we are still
> “more easily persuaded by one clear and concrete anecdote than by data and
> expert statistical analysis”. He says that, “an anecdote is a one off. It
> is not data. It is not science. It is dangerous”.
>
> This made me think about two things:
>
> Firstly, people such as Lydia Pintscher of Wikidata and Dario Taraborelli
> of Wikicite are working on projects that improve considerably the quality
> of Wikipedia and they could even accelerate world’s research.
>
> Wikidata is a collaboratively edited knowledge base:
> ...
>
> And Wikicite is building a repository of all Wikimedia citations and
> bibliographic metadata. The sum of all citations:
> ...
>
> Secondly, it also made me think about how this relates to the work we have
> been doing with AgreeList.com With AgreeList, we are creating a ‘platform
> for informed opinions’ that gathers the opinions of leading experts and
> influencers and favors the building of rational opinions on issues of key
> importance. Our first issue was ‘Brexit’ where we collected the opinions of
> almost 2000 opinion-makers on the impact of Brexit to the UK economy,
> immigration, politics, and education, and built a summary of opinions on
> both sides to inform the public during the referendum. In other words, we
> believe in the value of informed opinions over anecdotes and the data of
> who agrees on what and why can help us to build our own opinion. E.g. if
> NASA, the Royal Society, Obama, the Pope and a friend of mine who knows
> more about climate change than me think that it’s real and we should do
> more to tackle it, I believe it.
>
> Similarly, if I read something health-related, I can check the number of
> doctors who agree or disagree as fast as I see the number of likes on
> Facebook. If it is more than 95%, I believe it straight away. Done. I
> learned a new thing today. This way we could fight the fact that false
> health content seems to be more popular on social media and we could get
> informed of more topics than ever.
>
> When we are interested in a topic and have time, we read about it and
> contrast different points of views. But when we don’t have time or are not
> interested in something, we believe what our culture, friends and
> influencers say. And we are so bombarded with information nowadays that we
> can’t get informed about everything all the time.
>
> However, when we want to have an educated opinion about a complex topic
> such as Universal Basic Income, we can read the arguments and even go to
> the sources where we can find more information. We are still building up
> the database on Basic Income and it is currently biased towards opinions in
> favour given that it is easier to find them given how early stage the
> public debate and the AgreeList tool are, but you can see below what
> different opinion-makers say about Universal Basic Income via Agreelist:
> ...
>
> And when there are many opinions, such as on Brexit, we organise them in a
> board or summary that aggregates the arguments per categories.
>
> We can also filter them by profession, university, awards (e.g. Nobel Prize
> winners), etc. E.g:
> ...
>
> How did we get this data? First, the data from occupations comes from
> Wikidata. Second, the data of who agrees on topics such as these ones is on
> AgreeList. These lists are crowdsourced — people add influencer’s opinions.
> Users only need to provide a source, for example an article in the New York
> Times or the tweet of the person. Moreover, users of the site can vote and
> add their own opinions and, at some point, we could aggregate opinions
> automatically by semantic analysis. This way we might organise all the
> opinions in the world on key topics or statements. AgreeList or Wikiopinion
> could one day become ‘The sum of all opinions’.
>
> We can also play with Google BigQuery to do joins of AgreeList’s tables
> with Wikidata’s ones. For example, in order to get all Nobel laureates in
> economics that agreed or disagreed on Brexit before the referendum we did a
> query and we got:
> ...
>
> Extent is the degree to which they agree (at least for now it can only be
> 100=agree or 0=disagree). Therefore we got that from all Nobel laureates in
> economics that