Thứ Ba, 12 tháng 2, 2019

Waching daily Feb 12 2019

Do you also have interest in these books?

I want to find it

more than anyone else

Hmph! Find me?

After that, wipe me out completely?

I can't reach it

Master!

Master!

Help me get it!

Take it!

At first, after we received something in Wan Lu Sect,

We have to show it to the master

Could it be that this subordinate is the first?

Or is he a monk

with high virtues?

Or is it that he doesn't like to be so direct?

Let's change the method

Master!

Your eyes are so beautiful

They are like starry night sky

Your eyes are so beautiful

They are like starry night sky

Oh! It seems that he likes this type

Master!

I seem to be attracted by the eyes of the person

What's going on?

Wasn't he being seduced?

Forget it! This is enough for coming here today

Master! There is also another thing that I want to ask

Speak!

Recently my cultivating is not going well

Probably the inner flow in my body is not strong

Do you have any medicine that will help me to strengthen my internal flow?

Yup

Master is so good

Hey, Did you see that?

Don't speak! Don't speak!

For more infomation >> The best way to seduce your handsome teacher (Video with subs) - Duration: 4:08.

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The Relationship between Research Impact and Data Management (PARTHENOS Training Video) - Duration: 8:09.

Impact at the moment one of the core areas we're working on is collaborative

databases so many different research groups and individual researchers put

data in Excel sheets or access databases they've got a lot of them and they're not

necessarily taught the thought about research data management what happens if

my laptop breaks if the hard disk that this Excel spreadsheet is on can

multiple people work on the same spreadsheet at the same time or not so I

think there's a lot of things going on a lot of similar work being

done in different research groups across our faculty so if we can help to try and

help with good data management practices think about sustainability of that

research data so there is a three-year five-year funded project what happens

with the data afterwards what can we do to sort of think about that from before

the project starts what IT support do they need can we involve people in that

process to try and sustain that because it's often patchwork funding so

somebody's interested in a like say the southern Dutch dialects we're working

with some dialectologists at the moment so they've been going now 40-50 years

collecting questionnaires and how all the different dialect words in

Flanders are are used and this is a huge resource it's a huge longitudinal study

and how can we instill good data management practices in that so that

this legacy stay on for many years. I think that

through the work of data research data management for example we've had

training sessions we've had doctoral school students one doctoral school

student recently said well I want to move from spreadsheet hell to database

dreams and I thought we're going to be she's going to be publishing a blog post

on that soon but it's really somebody fighting with an excel sheet on their

personal laptop to making that into a user-friendly space where multiple

people can log in at the same time they can share their research data they can

say hey what do you think about this and we can you know do all this work

together so I think that step by step process

we just gained a database experts and ICT specialist to help us

out with this but I think that will be a huge impact for the different research groups within our faculty

Well one of the things as a researcher that I

hope to reach I mean as a researcher I'm involved in speech recognition and the

things around that going from human speech to written text for that we are

collecting a lot of data to build the speech recognition engine to do all

kinds of complex modeling for example if you talk about we do have a project now

for the Dutch parliament where we want to recognize everything said in

Parliament well the the language used in Parliament is quite specific I mean it's

not Dutch but they use other words than someone telling about a party last night

so that means to have an optimal result we need a parliamentary language model

that covers the way politicians speak in our national parliament so we are making

this model and we do it for our project but I hope that the research

infrastructure can help me to publish and to make this language model

sustainable I mean there are 200 million words and we are building right now the

language model and once it is there and it works and it increases the

performance or recognition engine I hope I mean we are going to the next project

and that may be something completely different but I hope that I can store

the language model and the data the language model is based on in a

repository and it will be there for the coming five to ten years that other

researchers

can profit from the stuff that we did and that's basically what I what we needed as researchers.

Research infrastructures can play a major role when it comes to software preservation and preservation of method

methodology forensic methodology of historic of historic computing systems

which have very individual forensic characteristics to be exploited by a

researcher this is not properly documented anywhere forensic experts

have a very short time frame of attention of historical attention

they are interested in how to get into a suspect system that is

three years old we have a totally different focus and that has to be

documented research infrastructures could preserve our software also

historical forensic software which well gets into and deals with historical

platforms for example or document procedures that were successful in

analyzing a specific kind of system these were these are things where

research infrastructures could play a role and I hope will play a role at some

point actually it is something that I would like to do at some point

if I look at a broader spectrum of digital humanities research

infrastructures the my personal understanding is that usually people

look at research infrastructures as repositories which can be served in a or

which can be which can be used and served in a structured way which are

which are being made more accessible by keywords may be data mining

technologies solar indexes so on and so forth as all fine I think that is still

too limited I think that research infrastructures should not be should

should not be just infrastructures that help us in discovering material but they

have to play a role in the research process itself

For more infomation >> The Relationship between Research Impact and Data Management (PARTHENOS Training Video) - Duration: 8:09.

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Data and Metadata (lego) (PARTHENOS Training Video) - Duration: 2:07.

meet LEGO Wonder Woman she's here to explain two of the most commonly used

terms in digital humanities: data and metadata let's take data first the word

data is generally used as a collective noun to mean facts or pieces of

information if we think of these pieces as bricks we can imagine the task of the

researcher is to sort through the pile of bricks to make connections.

A pile of facts can be organized into a data set; researchers use data sets to support their inquiries.

Let's move on to metadata; metadata is information about information

in this case it is information about the types of bricks

that have been used to make our structure for instance some are pink

with six studs and some bricks are blue clear with four studs this allows to

organize our bricks and he useful groups it's easier to start building when you

have this, instead of this. Computers think this way too this works in the

opposite direction also allowing us to filter objects according to the

characteristics described in their metadata we can drill down even more

into this metadata to filter it according to tags or types we know that

this structure or data set is made up of 186 pieces of these 35 or pink 16 are

green and so on the pink bricks can be filtered by characteristics such as how

many studs they have the same can be done with data sets each has additional

information to tell you about the data set as a whole how many items what

format they take this is the metadata knowing this information helps

researchers organize their own data sets and understand others

you

For more infomation >> Data and Metadata (lego) (PARTHENOS Training Video) - Duration: 2:07.

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Enhancing Individual Researchers' Impact (PARTHENOS Training Video) - Duration: 11:15.

I think it's a very complex question how research

infrastructures influence the impact of individual researchers and it's it's

complex and and difficult because the the whole system of how we measure

impact predates digital research infrastructures so the impact is usually

measured in on the basis of your academic publications and in these

methodologies you know journal articles usually weigh more than monographs and

in this there's a system in place which is incredibly capitalistic in its nature

that you have to deal with big publishers in prestigious journals etc

that system was in place before players like DARIAH and CLARIN came came on the

scene and the the the existing system doesn't take into account the fact that

we no longer produce only papers we produce increasingly digital annotated

editions we produce software we collect data so there's a whole range of

activities that are essential to the creation of it and the main

sustainability of a digital research infrastructure that are actually not

that they do not translate into you know points for promotion at a university etc

and I think this is one of the central challenges that actually we have as

humanists as scholars these days these days is to to transform the system

and call me a revolutionary but things will have to change now

I think the role digital research infrastructures cannot do everything on

their own they cannot you know we are not at the barricades we're not

squatting universities at this point in our careers but I think the the more we

develop they just have research infrastructures in the more the more we

show what kind of research is possible using digital methods the the the

academic academia at large will kind of have to adapt to this new model of

scholarly production so my answer is that I'm not sure I mean maybe it's not

the answer that you want to hear but I'm not sure that digital research

infrastructure are in a position to to influence the impact of individual

scholars as much as they should as much as they could but I certainly hope that that will change over time.

Scholarship now things are changing in this respect

as well and and I think things are better than they used to be maybe ten

years ago but but I think it still remains something that that actually the

you know people who are running digital research infrastructures will will have

to keep pursuing as a goal to explain that we have different modes of

production and that we need to evaluate what we produce in a different way

one model for instance already exists it's a tricky one but it exists it's called

post publication peer review okay so right now you submit an article usually

you submit an article to to a journal it gets peer reviewed it gets published

that's the end of the story a different model would be to write papers deposit

them in your University depository or repository or the digital research

infrastructure such as DARIAH or somewhere like that and then to create a

system where after you publish a draft people can actually comment and

help you improve the article now it's it's it's not as simple as it sounds

because a people have to find time to read and improve and some people might

not be that easy about or feel that easy about submitting or opening up their

unfinished work to the general public so in that sense I think there's there's

something that individual researchers can do as well is that try to think

about not striving just for perfection for the sake of career but striving for

more open and community oriented scholarly process as such I think that's

where we're kind of so on the one hand we would have advocacy and on the other

hand we would have scholars who decide to share more of their data and unfinished work to slowly change the way things work.

I think it's still about bringing people together so for example I've got an example of a social science

researcher she said she wanted to do some work on her laptop and her laptop

wasn't powerful enough so she said hey you don't happen to know if there's a

supercomputer at Ghent University and I said yes I do

so I was able to put her in contact with the Supercomputing Center and they

helped her they gave her training and how to use a supercomputer and then she

could process all the data, she was working on speeches doing network

analysis on speeches of European parliamentary papers so she was able to

do a lot of her processing on the supercomputer for example so I think in

a day to day impacts that hadn't a huge impact on her because she could do you

know instead of cranking on her computer she could do what the results they

analysis you want to do a lot quicker I think it's also to do with visibility as

well and making connections so for example we can put researchers in

contact with each other so from different

groups and for example we've got a new public library and digital innovation

center here in Ghent called the Croke so it's really nice because we've got the

public librarian underneath and then we've got the University of Ghent and

all various different research groups who are working on digital initiatives

that may not have necessarily worked together, the Ghent center for digital

humanities is also part of that group so we can start getting to know each other

understanding what our different research fields are and then work

together in different ways and making interconnections so the impact we're

starting to get to know each other at this stage but for example today I had

an international visitor and introduced him to one of the professors in in the

Croke and he they immediately thought oh yes we could do this and we could do

that and perhaps apply for funding for that so I would say that that's quite a big impact.

I think it's the idea of strength in numbers

if you've got research infrastructure which is in most cases well-defined

there's there's a structure around it with management and and coordination

that makes it easier for other researchers to latch on to this they

don't need to setup everything themselves they can just take advantage

of the infrastructure that's already there which makes it again a place where

a lot of input and feedback comes together from all these different

researchers so that it can even become a better infrastructure and people can

learn from interacting with the infrastructure but also interacting with

them with all the other researchers but also with the stakeholders of all these

researchers so it almost turns the pathway to impact in a more

interdisciplinary process which again from from a lot of

studies has shown that interdisciplinary work has a bigger impact because you

address more societal issues from different perspectives

and so in that respect I think it sometimes lowers the threshold for

certain researchers especially because if you term it as research

infrastructure it's closer to their habitat which is kind of the trick I use

when I talk about impact I start from their perspective on research it's it's

about your research so they may be just slowly tumble into impact because

they're going through a research infrastructure while there's an

undercurrent of outreach in the infrastructure if I'm making sense

so yes I do think that universities should invest in more of these accessible

research infrastructures that are being maybe even funded through structural

funds that in that way have sustainability to them and so they

become also recognizable for the outside world that's that's where we need to go

with our questions and there's a whole there's this critical mass addressing

questions so I think in that respect researchers should organize themselves

around these infrastructures and we should as a university strategically support them as well.

As a researcher who's willing to contribute to such

a project of course dissemination of your of your results is one big as one

big argument with a little caveat in there

the platform must be able to stress the individual contribution and make clear

whose contribution this is so that for example a researcher can later cite it

as their own work in order to not lose it for their own CV and so on and so forth

For more infomation >> Enhancing Individual Researchers' Impact (PARTHENOS Training Video) - Duration: 11:15.

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Ontologies Explained (in 5 minutes or less) (PARTHENOS Training Video) - Duration: 3:13.

So my name is Kristen, I lecture in digital curation at King's College

London in the department of digital humanities and today I will be talking

about ontologies in five minutes or less

so I like to think of ontologies as these kind of underlying systems that

give us the logic to draw relationships between objects or concepts or materials

that are in diverse collections so for example we can have paintings we can

have datasets we can have manuscripts we can have books that live in a museum or

an archive or a library or a data repository and we want to connect them

to you know the creator or the institution or the grant that helped

fund them and ontologies use a kind of grammar to do this they have subjects

objects and verbs so the subject would be you know for example your painting

that lives in a museum and your verb would express the relationship you're

hoping to capture right so saying it's a part of it was created by its you know

derived from you know a creator or a group of creators that would be the

artist that you're trying to kind of draw that connection between and you can

kind of build this up in increasingly complex ways so instead of saying you

know the painting was created by an artist you can say you know if you're a

historian and you're interested in cultures and events and places and

objects and you're trying to work with somebody say you know a physicist who's

knowledgeable about atmosphere and weather you can say you know this day

and time at this event you know these actors were involved in

certain things and we have our manuscript or data set that is telling

us about this and it relates to atmospheric data that these other people

created at a different institution and you can start creating these

increasingly complex relationships that are expressed using the logic of your

ontology so we have things like CRM that allows us to do this in

by also using conceptual models that allow us to articulate these

relationships so that we can become increasingly kind of specific when we're

saying what an agent is what an event is and kind of the types of relationships

and directions that were hoping to draw between them and overall it allows us to

organize things and organizing things allows us to share things and that's

basically what an ontology allows you to do in five minutes or less

For more infomation >> Ontologies Explained (in 5 minutes or less) (PARTHENOS Training Video) - Duration: 3:13.

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Must Watch New Funny |😂 😂Comedy Videos 2019 | Episode 03 Funny Ki Vines | by UTV HD - Duration: 2:28.

For more infomation >> Must Watch New Funny |😂 😂Comedy Videos 2019 | Episode 03 Funny Ki Vines | by UTV HD - Duration: 2:28.

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Giả Vờ Thương Em Có Được Không Remix - Dj Tom Milano [Video Gái Xinh] - Duration: 5:35.

For more infomation >> Giả Vờ Thương Em Có Được Không Remix - Dj Tom Milano [Video Gái Xinh] - Duration: 5:35.

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Best Funny Kids Slide Fails - Funny Kids Video - Duration: 3:36.

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For more infomation >> Best Funny Kids Slide Fails - Funny Kids Video - Duration: 3:36.

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Metrics for Measuring Impact (PARTHENOS Training Video) - Duration: 9:57.

That's something you need to change for the researchers grants then help them to

get something back from for all the effort that they put on collecting

cleaning and and publishing this data and I mean it's the same with the only

thing nowadays that counts is the number of publications, is the high-impact and things

like that also if you're a very good teacher and you

can make your students enthusiastic and that they should start doing the

things that you want them to do okay everyone likes that but you're not

granted because you're a good teacher and that's the same is the data if you

have a lot of data and make the data available to other researchers you are

helping them a lot but the university isn't granting that so in the end they

say well you know the amount of publication is below media so sorry we

have to leave you and that's and that is very difficult

outreach and impact for me out how true outreach is everything that we research

infrastructures can do in order to convey research results and new

methodologies to the academic community and beyond the impact of this activity

on research methodology on research results is measurable in terms of later

publications and in terms of the change of methodology that we can observe

reading research to put it very simply if we compare these two terms these two

words, concepts, ideas I like outreach I don't like impact I

have a big problem with the way impact is used these days for the accumulation

of academic capital bibliometric methods are highly questionable when it comes to

the humanities the problems you know are so numerous I don't even know where to

start when you're working on as a scholar in a small language you know

you're a literary scholar etc your community of scholars know your language

and they have to read your language and in the papers you write if we define

impact by simply bibliographic methods and hot you know so-called high-impact

journals we are really privileging those who work in big languages, those who work on English and

I think that's that's a very dangerous trend for the humanities so in that

sense I'm really not not a big fan of impact and I must say that in my career

which is which has been maybe unorthodox in certain ways I always wanted to work

on things that I'm interested in and I really didn't care

so much about the kind of impact that I've been talking about so far

Now that's number of publications of course and also recognition in the academic

world, which is not always the same I mean because that's what I find

important that I that I have the feeling that I've contributed something to our community.

Research infrastructures are just a means to an end, it gives people

maybe the excuse to go further in what they're planning to do the biggest

barriers which are more on a systemic level you can provide as many research

infrastructures as you want if you don't change the system through which

researchers are being evaluated through which research is being evaluated it's

kind of a window-dressing exercise so well that's that's that's my job

basically I have to change the system so what we're looking into is changing the

promotion and recruitment criteria for professors changing the allocation model

within the university changing how research is funded essentially and

trying to introduce strategic goals for interdisciplinary research centers

focusing on societal impact it's little things like introducing impact

paragraphs in our own funding mechanism it's making lay summaries of PhD

dissertations mandatory there's a whole panoply of things that you can do as a

university investing in research infrastructure is just one thing of

these things the unfortunate thing is you need to

work on all these levels and then there's a whole layer of walking the talk

as it were, communicating about the success stories of research impact

and I think in in Flanders we're in this interesting position that it's not being

demanded top-down that we invest in impact of research well at least not

societal impact of research it's all about jobs and growth and money so the

system that is top-down being imposed upon us is still very much geared

towards scientific impact so we don't have a REF that's kind of what I'm

saying but at the same time that's I think an advantage because we still what

they've lost in REF which is namely the administration and the management of REF

is putting a bigger burden on researchers than the question what are

we in fact doing what's the difference we want to make in the world we're still

at the level that we can introduce all these policy elements from this age-old

question what do we think is important what should universities be doing what

should research be about but of course you need the stick and the carrot so

what I'm saying is we still have this I think it's a bottom-up rrive now

and that's that's a good thing and we need to take our responsibility as

universities then to change the system and we shouldn't wait for top-down to

enforce research evaluation or research funding allocation with impact in it so

we still have time to try some things out and do it without clear definitions

on this is impact this isn't impact so I think we're in an interesting position at this time.

Since I'm working a lot on societal impact and how you can measure

it and how you can enable researchers to work on societal impact and so and so,

that's a trending issue as many researchers know and then I found out

about the the impact of matrix from DARIAH, which is I think a very good

example of distinguishing between different kinds of impact so that's

really useful it has some very very specific examples but but again I think

we have to take it to the next level I think we still

sense these different kinds of impact are so diverse I think we really have to

think about dimensions of impact and I think the impact of metrics could be

improved and especially if we work together with different researchers from

different disciplines and social sciences and humanities we could improve

impact metrics and really develop it towards a tool that is useful when we

talk with researchers about developing for example a societal impact plan because

from my perspective that is fundamental we want researchers to to achieve

societal impact but that also means that from the early beginning before they

start doing their research we will have to ask them how please think about how

you will achieve societal impact that's the first question of course the second

thing is how well didn't eventually report on how did they achieve societal

impact and many people know the the impact case studies from the research excellence framework in the UK that's a very good I think a very good

way to describe the process towards societal impact but a tool like like the

impact metrics could if it if it could be taken a step further we could even

offer researchers different indicators for societal impact and then for example

we could offer researchers a choice to choose different indicators and they

could then actually go and try to measure societal impact in a very

specific way so and that's that's I think one well dream is maybe a little

bit exaggerated but still I think the metric is a very good first

step and we should certainly think about how we can take it to the next level

you

For more infomation >> Metrics for Measuring Impact (PARTHENOS Training Video) - Duration: 9:57.

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The Infrastructural Turn (PARTHENOS Training Video) - Duration: 12:22.

so having talked a bit about how we might define a research infrastructure I

now want to step back a little bit and give you some of the history and some of

the sort of the theoretical underpinnings to my understanding into

what I would see as a general understanding of what research

infrastructure is in the modern era so before we can get to the modern era

though we have to look at where this whole idea comes from and it's a it's a

very interesting idea that comes across in this particular ESF report because

they actually look at research infrastructure as not something that

came up specifically in the sciences but actually if you trace it all the way

back if you want to find the beginning of the

idea of a research infrastructure or knowledge infrastructure you're really

going back to the Museum and the Library of Alexandria so you're talking

about something that actually is coming from the ownership of the humanities

originally but of course time has moved on and the needs for research

infrastructure have changed very much over the years and in particular in the

time after the Second World War when we saw a technologization of research but

there's also again a slightly smaller time horizon that is invoked in

this idea of the law now of research infrastructure and so for these writers

it doesn't go all the way back to the Library of Alexandria but they see it as

actually going back about 200 years and that 200 year time span is based on an

understanding that there was two things that caused a need for research

infrastructure one of which is the exponential increase in information

gathering activities by the states so this kind of creation of official

archives and statistics at a more massive scale than had been done before

but also the idea that the the knowledge workers were there and that there was an

accompanying development of technologies and organizational practices

they were able to sift and store all this information so that there really

was both the information and the ability to deal with the information and those

two things started about two centuries ago. But if we want to look at what we deal

with in Europe as a kind of a modern context for the

development of research infrastructures then we really need to go back about 10

years now to the year 2006 because for me 2006 was a big turning point we saw

two major publications released in 2006 one in Europe and one in the US and

those mark I think the beginning of our current understanding of research

infrastructure. So in Europe we had the publication of the SP roadmap now this

road map was created at a European level to describe the scientific needs for

research infrastructures for the next 10 to 20 years and I should say that this

has been updated and extended in its time horizon and what the European

Commission wanted to do with this roadmap this European strategy forum on

research infrastructures, is they wanted to say well research infrastructures are

big they're important and they're best used as a shared resource so to try and

really bring that together at a pan-european level and to coordinate

investment was going to bring great value for researchers across

Europe so this was the the European vision and there were a number of

different entries onto this roadmap in 2006 including what we now know of as

the digital arts and humanities research infrastructure or DARIA and also the

research infrastructure for linguistics and language resources which is known as

CLARIN there was another entry on that roadmap at the time which was a European

research Observatory in the humanities that was actually never realised which

is an interesting question to discuss afterwards if we so choose but the other

thing that happened the other publication that appeared in 2006 was

the the report in the US called our country cultural Commonwealth lead

author of this was a man named John Unsworth now this was itself a reaction

to another report which is commonly known as the Atkins report now the

Atkins report was looking at research infrastructure across all the

disciplines across all the sciences across all the areas whereas our

cultural Commonwealth was intended to actually bring out the specific needs of

the arts and humanities of the kind of the cultural side of research

so that was something that really kind of took the discourse out of that

scientific mode and actually bedded it into that culture need and what's really

interesting about this I find is that if you look at some of the things that were

actually going on in our cultural Commonwealth you'll see that many of the

things that Unsworth was calling for at that time are things that we have yet to

actually deliver on -- that we have yet to actually achieve but that we can

evermore recognize as important for the delivery of research infrastructure so

he was calling for investment he was calling for public and institutional

policies to foster openness and access of course we live in the age when open

access and open research data are becoming ever more important both to the

funders but also to the scientists themselves to cultivate leadership to

build human capital I suppose would be another way to say it

to encourage digital scholarship I think that's something that has been happening

incrementally but also to establish national centers to support scholarship

of course this is something that you could really see those European research

infrastructures as doing and also to create extensive and reusable digital

collections and this is something we are still struggling with so many of the

things that this report which no matter how old it is is really still very much

at the at the cusp of what research infrastructure needs to do for the

humanities have not been delivered yet and they still provide us with a very

good road map pointing forward but of course a series of actions doesn't

necessarily give us what we need in order to actually be able to deliver we

also need some basic understanding, and I've already mentioned this particular quote

the idea that a research infrastructure gets you below the level of the work

because this is something that from my point of view you really need to

understand that you're not creating a tool or something that's going to be

time limited it's something that actually is going to have a very broad

applicability and that will be very easy for many different kinds of scholars to

use in their work. Another thing that we need to bear in mind as we're

taking this kind of theoretical approach to well okay if we need to deliver on

these various actions to create an infrastructure what

else do we need to be wary of what we need to be mindful of as we do that

there's also the question of what's the role of the digital library in all of this and

that's one thing that we're seeing and I'll be speaking more about the

relationship between research infrastructures as we know them in the

European kind of research infrastructure context and the relationship to digital

libraries digital archives in one of the later sessions but the thing to remember

is that digital libraries are meant to do the same things that libraries do

only for digital objects whereas research infrastructures take much more

of a user driven a methodological approach and whereas these would have

had lots of pressure to be drawn together in earlier phases of our kind of

development as a research culture now there's much less of that gravity to

hold them together so what's happening is for example digital libraries are

struggling to a certain extent to maintain what's produced by scholars if

a scholar produces a website if a scholar is producing epubs or anything

like that, we're moving from that that kind of shelves mentality to a racks mentality to

the idea that there's a data side of things in many institutions we've seen a

coming together of the digital library or even the library services and the IT

support services and that is a recognition of this but it's by no means

happening everywhere now we also see that the digital library is struggling

to a certain extent to enable new methodologies

we're moving for a reading paradigm to potentially a distant reading paradigm

and from maybe a history paradigm to a transnational history paradigm um many

of the research libraries that I would know in the research archives I would

know are incentivized to be a national institution or a regional institution

and the idea that you have users coming in trying to do transnational history to

try to what to bring their collections together with those of other similar

organizations this becomes very difficult for those institutions to

necessarily deliver on um they also find it difficult to be open again for some

of these same reasons how are they incentivized to serve users somewhere

else in the globe not the taxpayers that might be paying to support the National institutions and how do they develop the kind of skills and the kind of

the kind of skills and the kind of mentality to understand that their own little silo is actually not going to be

the thing that the user might want that the user may want to bring some of their

stuff together with some resources from somewhere else and maybe a database

created by themselves and something from another place entirely all of these

things in different formats this is what we call the data soup mentality so how

do we make it so that this data soup can be can be productive can be delivered by

the the traditional institutions and then finally there's this question of

the upfront investment mentality the idea that every object in a collection

should be recorded but as the the difficulties continue to compound with

different kinds of formats and an increasing level of things being brought

into the digital library this is more and more of a of a challenge for them so this brings me just to a quick look at a research infrastructure project I

know very well this is the actually the the data architecture of CENDARI

infrastructure so the collaborative European digital archival research

infrastructure and I just want to show this to you because I think in some ways

the directions where the research infrastructure is moving are quite

interesting and we see this as a very similar kind of architecture being

proposed for the European science open cloud which is going to be a major

resource for the sharing of research data but what you notice when you look

at this picture is that you have a number of objects and things at the top

which are the presentation layer and that presentation layer consists of the

kinds of tools and environments where the researchers will use the

assets or will manipulate them interrogate them curate them do whatever

they need to do to create knowledge and then coming in from the bottom we have

the the various data sources coming in and in that that sort of set of

acronyms which I'm not going to break down for you because it would take far

too long and perhaps not be very interesting but there is an internal

repository for data items there is a triple store which has these kind of

linked data assets that are used to enhance the data that's

there there is input from a meta search engine developed specifically for

medievalists and then what you have in the middle and this is the most

important thing about this is that brown line that goes all the way across and

that's the API so essentially what you have is you have a very large number of

data sources coming up to the bottom you have a very large number of environments

and tools you can use to work with those resources coming from the top and then

in the middle you have just one thin layer that makes it all possible so this

kind of hourglass shape I think that's what we're going to see more and more

coming in to the development of research infrastructures as we accept the fact

that people are going to want to work with different kinds of data and they're

going to need to to deliver the kind of research they want to do and they're

going to want to use different kind of tools and they're gonna need to to

do the kind of research they want to do and then in the middle you need

something to make everything talk to each other and that's really the model I

would see for research infrastructure that would be quite different from a

digital library so we'll come back to some of these issues in later sessions

especially the relationship between the infrastructures and the libraries but

we'll hold here for now

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