Open Geodata Digital Spaces
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00:00
Offene MengeMinkowski-MetrikCoxeter-GruppeDigitalisierungOffene MengeMereologieMomentenproblemMAPCASE <Informatik>GruppenoperationKontextbezogenes SystemDifferentialgleichungSpeicherabzugMixed RealityDifferenteProjektive EbeneDiagramm
01:20
DigitalsignalTouchscreenRandwertBaumechanikVektorpotenzialGebäude <Mathematik>HypermediaInformationsspeicherungMinkowski-MetrikVirtuelle MaschineGeradeAggregatzustandSoftwaretestExzentrizitätDifferenzkernStrömungsrichtungDivisionMapping <Computergraphik>SpeicherabzugGruppenoperationCoxeter-GruppePerspektiveWurm <Informatik>QuantenzustandObjekt <Kategorie>Quick-SortFlächeninhaltMAPTouchscreenHypermediaProdukt <Mathematik>ComputerspielBildschirmmaskeQuellcodeWhiteboardPunktGebäude <Mathematik>DifferenteComputersicherheitDemoszene <Programmierung>SystemaufrufExplosion <Stochastik>Wurzel <Mathematik>BildverstehenDigitalsignalAnalogieschlussMigration <Informatik>VektorpotenzialFacebookAnalysisOpen SourceDigitalisierungAlgorithmische LerntheorieDialektAlgorithmusBildgebendes VerfahrenMultiplikationsoperatorRandwertNeue MedienProjektive EbeneBitSystemplattformEinflussgrößeInformationsqualitätPolygonNeuronales NetzComputeranimation
10:09
DigitalsignalVektorpotenzialPunktHypermediaMinkowski-MetrikDienst <Informatik>MathematikDatenverwaltungAggregatzustandDifferenteSystemaufrufRichtungMaßerweiterungARM <Computerarchitektur>KonditionszahlArithmetisches MittelZweiEntscheidungstheorieKomplex <Algebra>Coxeter-GruppeOrtsoperatorGesetz <Physik>Notepad-ComputerCASE <Informatik>GefangenendilemmaInformationsspeicherungEndliche ModelltheorieFlächeninhaltFrequenzsinc-FunktionLesen <Datenverarbeitung>Formation <Mathematik>BeobachtungsstudieInstantiierungRechter WinkelEinsMessage-PassingGamecontrollerMixed RealityOntologie <Wissensverarbeitung>SoftwareentwicklerTwitter <Softwareplattform>FacebookSichtenkonzeptObjekt <Kategorie>MAPDigitalisierungRandwertDifferentialgleichungVektorpotenzialVerschlingungSystemplattformInformationsqualitätVersionsverwaltungStatistische HypothesePhysikalischer EffektProdukt <Mathematik>Natürliche ZahlDialektDifferentialGüte der AnpassungInverser LimesComputeranimation
18:58
SprachsyntheseMAPOffene MengeComputeranimationBesprechung/Interview
19:22
MinimalgradFakultät <Mathematik>SpieltheorieBaumechanikProzess <Informatik>InformationPhysikalischer EffektOrdnungsreduktionFrequenzWechselsprungBesprechung/Interview
20:17
HilfesystemOffene MengeMinkowski-MetrikDigitalisierungProzess <Informatik>Mixed RealityBesprechung/Interview
20:41
DifferenteCodierungSoftwareentwicklerEntscheidungstheorieBesprechung/Interview
21:53
GruppenoperationOffene MengeMAPProjektive EbeneZahlenbereichRückkopplungDatensatzStandardabweichungSchießverfahrenBesprechung/Interview
22:48
RechenschieberUmsetzung <Informatik>Wort <Informatik>DifferentialgleichungGeradeVollständiger VerbandTwitter <Softwareplattform>Projektive EbeneTypentheorieKollaboration <Informatik>KoroutineOffene MengeComputerspielOrtsoperatorInformationWellenpaketWeb-SeiteEndliche ModelltheorieProzess <Informatik>Güte der AnpassungRoutingPhysikalischer EffektBesprechung/Interview
25:07
InformationWeb-SeiteMultiplikationsoperatorBesprechung/Interview
25:40
Hidden-Markov-ModellBesprechung/Interview
26:11
Workstation <Musikinstrument>ForcingGüte der AnpassungMAPOffene MengeFokalpunktMultiplikationsoperatorBesprechung/Interview
27:19
DifferenzkernMetropolitan area networkDifferentialgleichungMAPDialektUngleichungProdukt <Mathematik>Güte der AnpassungComputerspielGoogolDienst <Informatik>Besprechung/Interview
28:07
Offene MengeFächer <Mathematik>MAPBesprechung/Interview
28:31
Computeranimation
29:07
Computeranimation
Transkript: Englisch(automatisch erzeugt)
00:05
Hello everyone, my name is Mohammed Saleem and I am here to present OpenGIT data digital space and taking the history of OpenStreetMap. I belong to a startup that is called OpenGI science research lab that is in Yavuzan, Netherlands, which I am a lead researcher of.
00:29
So, I am presenting today a small part of a larger project that is called OSM Ritopia, where I am trying to define how the world map should look like more ethically and not
00:46
taking into account the modelled or generalized approach and more on context and qualitative and mixed design approach. So, for this presentation, I would like to present that how OpenGIT data digital space is an important concept and
01:07
how we can understand that, understand different aspects, social or non-social aspects of OpenStreetMap and Geo Data in general.
01:20
So, let's first go through what is a digital space. Before that, we have to break down or segregate space in digital. Space is where the physical space and the activities takes place and experience takes place and where we can see objects from our physical eyes.
01:42
And that's what I find from my research project. And digital is anything that's in the space and then you put it on the digital screen for analysis or for any other reasons. And digital space is where the activity that is still happening and that caused the creation of that digital and specifically maybe at the maps.
02:08
And this is why it is important to define digital space in Geo Data. And when it comes to OpenGeo Data, it should be exaggerated to define or to understand that.
02:25
But to define, to actually understand first. If we define it, it will be really a generalized approach. So, I will propagate that it should be understood before it can be defined even.
02:40
So, whether the digital space in OpenGeo Data exists and how it exists, that I will explain in the next slide. So, in summary, what I said here is that there is an analog. Analog means what is on the known digital side like buildings.
03:03
If I consider Geo Data, then it would be, analog would be buildings, roads or anything in particular that can be converted into a data and converted into a digital data. And now it says definition of analog data and digital data that I will not go into depth.
03:24
And still I don't have an answer or understanding of that, that what is digital data and what is analog data. That's also a form of debate that we should also consider. So, what happened is according to this understanding, there is something analog.
03:43
And, for example, buildings is converted into a digital and the data is produced and then the digital is produced. Sometimes digital is produced, for example, the media attention and other digital forms of gaining potential gains and opportunity building.
04:01
And then people gather up to create data, for example, migration crisis is forced into the digital and then into analog, not particularly a certain migration crisis. Some migration crisis is caused by the digital media or social media. And then it's went to the analog to create data from certain form of activity,
04:26
from the mappers or for the machine learning algorithms were created from the manual work. And then this is converted into a digital data. So this is what I mean by analog and digital. And sometimes it's always the loop.
04:42
So from this we understand, I also understand that this creates different data and especially when I said open digital data, then it means that there are different stakeholders and different steps that creates the data. So the different steps that encourages the data to be produced is a form of analog and it's a form of space.
05:09
And it happens in the space. So for that reason, we need to understand the data production. There is no one way data is produced.
05:22
There is no general way the data is produced. We should have to understand better how the data in different regions and different platforms are produced. Because it will lead us to understand better ethical boundaries. Because if we generalize certain definitions of data production or ethical boundaries that is only for the global north,
05:49
then the global south will suffer. And research has shown that as well. And finally, with the different data, there will be different data quality measures.
06:04
And I have to understand that what data quality means for different regions and for different platforms. For instance, I'm taking OpenStreetMap. So let's talk a little bit about what is OpenStreetMap. So OpenStreetMap is a map of all worlds. It is freely available and open to anyone that wants to contribute to it.
06:26
So what happens is that these lines, these are lines and polygons and multilines and features, that's called features. And these are considered as something that is digital.
06:42
And that means it is created through machine learning or artificial intelligence algorithms or by manual mappers that are added or clicking the data into the OpenStreetMap. But from our understanding, these lines, these points, these objects does not only represent polygons and lines,
07:07
but it represents something, it has some emotional and entity value and featured value and history. To understand that how it was produced, whether it is produced, was it a better data when it was produced?
07:28
Of course, when we look at the measures from the global north, it represents that it is a better data. So from my perspective, these points and polygons have a certain value and has been created when some certain activity happened
07:45
or certain attention was taken into account and then they were created. They were not just created out of nowhere. So this is needed to understand that when these activities take place, why I am asking this question
08:03
is because to know what are the motivation of the mappers and what happened in the space that causes something to change. So we need to understand that space that causes that digital to really understand what actually happened with data production and what ethical boundaries should be taken care of while producing that data.
08:24
There are various explanations of that activity. So let's go through the activity approach. There is an activity approach and there will be a motivation approach and there is also a potential gain approach.
08:42
Then finally we will look at the users. Activity approach is when the data is produced. So the data is produced when disaster happens. So activity approach relates to when is the data added.
09:02
So when this activity took place, for example, the disaster and the humanitarian crisis or opportunity building, for example, commercial opportunity like Uber and via Facebook is using the data of open-source data and producing their products to their users. And media attention, there is a huge media attention about refugee crisis,
09:24
huge commercial opportunity building came into being and from digital it becomes analogue and then it can become a host of data. So this form is still limited. Maybe there are more activity approaches there.
09:43
Secondly is the motivation approach. So usually these approaches are interconnected but not all the time it should be interconnected. These are just categories. So when this also happens, there is a disaster mapper that motivates them or motivates themselves and add the mappers.
10:00
And mapper and attentionist wants to map and then they map the entire area. Images mappers are also mappers that map their own area. And I'm going into details because this is not the topic I want to discuss more. And then there are career mappers that wants to improve their career
10:21
and to learn skills and commercial actors that are adding data for their own commercial use for their users, for example, Uber and Facebook. Sometimes this also can be considered as a potential gain. Why I'm asking this? Because this is motivation and potential gain should be segregated somehow
10:41
because sometimes the potential gain is something else and the motivation is something else. For example, the case of Foxes Bazaar that I presented in my previous presentation, I would like to invite you to see that. I will send the link as well that in Foxes Bazaar, the data has been produced by disaster mappers,
11:02
not disaster mappers, but humanitarian crisis mappers, crisis mappers, let's say. And their higher motivation is humanitarian. While the commercial actors are choosing it for the potential gain and using the data to present it to the decision makers of Bangladesh and using it for repressive refugee control.
11:27
So this should be differentiated in certain cases and it doesn't need to be generalized in the first place. And then because this varies with the usage,
11:46
because potential gains are the usage of the data in digital world by creating discospaces. So these potential gains are mainly monitored and the value that is added to them is whether they can make money or not.
12:04
If we remove the money, then it will be a motivation for the cause. There's always incentives. This is really complex. The conflict between potential gains and the motivation is complex, homogeneous and plural in nature. There are various ways of looking at the differentiation between them.
12:24
But when it all comes to the usage. So in order to understand the quality, you need to understand the usage. So I am not a fan of or have a provocation that quality is not always what end users require.
12:42
As I mentioned in the previous case study that your end users need a repressive control for the refugees, for instance. This is a really huge topic in the data science now that whether the data of refugees should be shared or not. So this is really a provocation.
13:02
So I come to an conclusion that quality is not always what end users require. It has continuously been created like this and this provocation should be taken into account that it's not always what end users require. And the quality, how we define it should be according to the usage.
13:21
Ethical boundaries should be maintained for its usage and it should not do any harm. So far, how does our digital space looks like? So it's an activity, a certain activity happened, a disaster happened and then there is a motivation or potential gain.
13:44
Certain actors, usually multiple actors, they take charge and produce data and then there is a usage. Usage is risk analysis, getting it into place, routing, everything.
14:03
So the world ends up in the usage. Our digital space looks like this and it's always the change in some cases overlaps. It's not a model, it's just how we can develop certain understanding of it.
14:20
But limiting approach to this is one of the feminist researchers says that the world looks different if you start from the periphery rather than the centre. So if we start from the activity towards the usage, the understanding that we develop about the digital space of certain case study would be different if we start from the usage towards the motivation and the potential gain.
14:46
So this needs to be understood as well that if we design, I'm not in front of the model design. So this is not a model approach, this is not a model thinking. So this is how we can understand what's happening in the data production.
15:08
And it varies with different cases and with different case studies and with different platforms. So with this understanding, we will get different views, different understandings from it and we understand things quite differently.
15:24
That's actually one of the hypotheses I'm using and I'm not trying to limit the approach only in one direction by moving it to both directions. We understand what understanding we can get from both ways. But the limitation of course is that it varies with different regions and approaches.
15:44
And if we get one understanding, we cannot apply that understanding to anything else. It's really qualitative and to some extent mixed design and transdisciplinary because there are various disciplines involved in it. Like stakeholder analysis, stakeholder management, GI science and social science and philosophy of science.
16:04
When I think about that object represents something, it's about coming from object oriented ontologies and objects are living things or not. In the space, only the living things can add into digital or non-living things as well can add to the digital.
16:24
So it varies with different regions and with different approaches. So finally, what we will get out of this. We will understand how the data is added in multiple ways. There is no one way to add data, of course.
16:44
And there are multiple activities that happen and how they differ from each other. And how we should not generalize the data production and data quality definitions. This is how we should understand instead of defining it.
17:06
Defining it is a good way for practitioners, which is fine, which is right. But there is more to do the data production than just defining it, analyzing it. So because it can cause certain harm as well.
17:23
Because when we are using the disaster mappers to add the data for refugee crisis, their motivations were different. While the parental gains that were getting from the commercial actors were different, I mean, in the end, it was causing harm. Because we didn't have any understanding, we were just taking into account what the end user means.
17:49
And finally, that would reduce the data injustice. For instance, in Haiti case, data is only added when there is a disaster. Before the disaster, nothing was added.
18:01
So we need to understand that what attention, what media attention and other attention caused certain areas to be mapped. Thank you very much for attending the presentation. Please reach out and one of the gains from this presentation is I'm
18:23
looking for people participant to answer my questionnaires to understand the digital data, the digital space better. And also, if possible, I would like to invite you for interview. Please reach out if you're interested. Just send me a message on Twitter or LinkedIn or anything.
18:41
I would be happy to accommodate. And it would be helpful for me to understand different point of views on digital space and in general a positive map. Thank you very much. And we're met.
19:14
Please tell us more about yourself and about your background and how you are connected to open street map.
19:21
OK. Thank you, Mr. My background is like I have a master's degree in spatial engineering from faculty of information science. So my background is really mixed with civil engineering and also technical science and GIS. But what I most like is multidisciplinary to do stuff like for transdisciplinary and multidisciplinary from
19:43
from the technical science and also to some social science stuff and to combine them and to see how how to how these two connects and what can we benefit from it. So currently I have a job from nine to five that I do for money.
20:01
And from five to nine, I do it for passion here in my startup. And also on the weekends. So it's it's kind of a nerdy game for me to do it. But sometimes I get a lot of interesting things discovered. And so that's me. OK. So I think your timetable is similar to to many of people that are joining now.
20:24
So they have their day job and then the hobby that they work on. And how does this understanding of digital space help open G.U. developers? Can you tell us more about that?
20:40
This is this is why I think for open G.U. science developers, we need to understand that their data is open and anyone can use it and their codes are open and anyone can use it. So it's it's important how how this understanding will help that how different users are going to use that data and how
21:05
they can make sure that their their their codes or their their data is not causing anyone harm and any public harm. And to understand more that that how the value has been created for different people and different people creates that
21:24
value in a different way, because sometimes developers are in the global north and we are developing something for global south. And we need to understand that there is a gap and of understanding of the usage. So they will have this will help for them to understand that gap as well and to make more ethical decisions.
21:48
Not a problem, but it's just a distant distant understanding. Yeah. OK. Yeah, that's right. And do you think that this topic would be a good topic for an open street map working group or is there something like that already?
22:04
Well, there is not yet too much majority of this project, and I would really like to present this to my working group. And I usually attend these in those talks. And this is definitely a topic for them.
22:20
And I would really like to work with them as to reach a certain majority. And for this talk, I would like opinions and I would like feedback from the people that are watching now and I will be watching in the future. To what do you think about OpenStreetMap and how OpenStreetMap could be looking more ethical or open standards to be more ethical in general.
22:48
OK. Yeah. So maybe with a recording of your talk, you can reach out to the to the rest of the OpenStreetMap community who is not there today and go on with a discussion. And another question, how can people join the conversation and get in contact with you?
23:07
I think I give my contact in the last of my slide. And I would really like people to come and talk to me about what they think about OpenStreetMap and what do they think that how the data was created and how do they contribute to OpenStreetMap?
23:26
Because I really want people to join this project and probably work in collaboration with me. I would really interested and they just need to reach out to me. I'm a very open person and I have like routine that would match their routines because five to nine or the weekends.
23:45
So we can talk and how we can collaborate. The first thing is that I said there's something that is not attractive for joining my project or joining my my foundation is that it's still nonprofit. So there is little to no money.
24:02
So I do it for passion. And I what I really want to do is that to create a better understanding of data ethics that is for science. And because I think that there are a lot of problems that has been caused by generalizing the data and data models.
24:22
So. Sometimes it's it's it's in opposition to the big cooperation. So that's why it's sometimes I sometimes it's a bit tough to get funding. So that's what I mean. But even if you don't want to collaborate because of any of the reasons.
24:42
But I would really like to talk to you, to anyone who is interested in talking with me for half an hour or just to fill a questionnaire that I have developed. And that questionnaires will be developed like for one week. And please reach out in Instagram or Twitter or anywhere. So, yeah, I can go back to the room and I can type my contact details because I'm really desperate for people to contact me.
25:05
Sorry. OK, that's good. So people people can stay here. We have a whole whole way room where people can discuss with you in person after your talk. And on the submission page of your talk, you you added also information.
25:25
So people find all the information to to contact you, I guess, and we can chat it also in the chat. OK. Anything else we could discuss? We have some more time, three minutes to go.
25:40
So. Go ahead. OK, let's see. Mm hmm. More questions from the audience, maybe people can still ask questions, but. There are no questions there yet.
26:10
Maybe like a question for the audience, then if you're not going to ask me a question, I'm going to ask you. So maybe if anyone can write like how do they use OSM or what?
26:23
What is OSM to them in the chat? And I would be really interested in doing that. Yes. You are free to to go on with a discussion in the in the chat, in the geospatial deaf room. That's no problem. And can ask questions there. And I think we have these many million open street map users all around the world.
26:46
And I guess that everyone has a different focus and maybe you have different interests in what what to map and what to do with open street map data. And maybe like this, you don't have in mind that maybe with all with the data that you provide in open street map, maybe you can harm other peoples.
27:14
So that's good that you provided this.
27:25
Yes, you started this discussion and. Yes, this discussion is quite important before it gets exploded with data. I think it's explored with data and and there is first there is inequality in production of data.
27:46
And secondly, there is a divide. Inequality is that there are no data in some regions. There are a lot of data in other regions. And then divide is like. Certain certain certain people from really developed countries starting to map countries in global south and their own understanding.
28:08
So, yeah, that that that's motivates me to develop this understanding better. I think open street map, on the other hand, is a way to bring the global populate community together.
28:22
And that's great to to be be able to to map in a region where you don't live. And the other way around, you could manage.