下載App 希平方
攻其不背
App 開放下載中
下載App 希平方
攻其不背
App 開放下載中
IE版本不足
您的瀏覽器停止支援了😢使用最新 Edge 瀏覽器或點選連結下載 Google Chrome 瀏覽器 前往下載

免費註冊
! 這組帳號已經註冊過了
Email 帳號
密碼請填入 6 位數以上密碼
已經有帳號了?
忘記密碼
! 這組帳號已經註冊過了
您的 Email
請輸入您註冊時填寫的 Email,
我們將會寄送設定新密碼的連結給您。
寄信了!請到信箱打開密碼連結信
密碼信已寄至
沒有收到信嗎?
如果您尚未收到信,請前往垃圾郵件查看,謝謝!

恭喜您註冊成功!

查看會員功能

註冊未完成

《HOPE English 希平方》服務條款關於個人資料收集與使用之規定

隱私權政策
上次更新日期:2014-12-30

希平方 為一英文學習平台,我們每天固定上傳優質且豐富的影片內容,讓您不但能以有趣的方式學習英文,還能增加內涵,豐富知識。我們非常注重您的隱私,以下說明為當您使用我們平台時,我們如何收集、使用、揭露、轉移及儲存你的資料。請您花一些時間熟讀我們的隱私權做法,我們歡迎您的任何疑問或意見,提供我們將產品、服務、內容、廣告做得更好。

本政策涵蓋的內容包括:希平方學英文 如何處理蒐集或收到的個人資料。
本隱私權保護政策只適用於: 希平方學英文 平台,不適用於非 希平方學英文 平台所有或控制的公司,也不適用於非 希平方學英文 僱用或管理之人。

個人資料的收集與使用
當您註冊 希平方學英文 平台時,我們會詢問您姓名、電子郵件、出生日期、職位、行業及個人興趣等資料。在您註冊完 希平方學英文 帳號並登入我們的服務後,我們就能辨認您的身分,讓您使用更完整的服務,或參加相關宣傳、優惠及贈獎活動。希平方學英文 也可能從商業夥伴或其他公司處取得您的個人資料,並將這些資料與 希平方學英文 所擁有的您的個人資料相結合。

我們所收集的個人資料, 將用於通知您有關 希平方學英文 最新產品公告、軟體更新,以及即將發生的事件,也可用以協助改進我們的服務。

我們也可能使用個人資料為內部用途。例如:稽核、資料分析、研究等,以改進 希平方公司 產品、服務及客戶溝通。

瀏覽資料的收集與使用
希平方學英文 自動接收並記錄您電腦和瀏覽器上的資料,包括 IP 位址、希平方學英文 cookie 中的資料、軟體和硬體屬性以及您瀏覽的網頁紀錄。

隱私權政策修訂
我們會不定時修正與變更《隱私權政策》,不會在未經您明確同意的情況下,縮減本《隱私權政策》賦予您的權利。隱私權政策變更時一律會在本頁發佈;如果屬於重大變更,我們會提供更明顯的通知 (包括某些服務會以電子郵件通知隱私權政策的變更)。我們還會將本《隱私權政策》的舊版加以封存,方便您回顧。

服務條款
歡迎您加入看 ”希平方學英文”
上次更新日期:2013-09-09

歡迎您加入看 ”希平方學英文”
感謝您使用我們的產品和服務(以下簡稱「本服務」),本服務是由 希平方學英文 所提供。
本服務條款訂立的目的,是為了保護會員以及所有使用者(以下稱會員)的權益,並構成會員與本服務提供者之間的契約,在使用者完成註冊手續前,應詳細閱讀本服務條款之全部條文,一旦您按下「註冊」按鈕,即表示您已知悉、並完全同意本服務條款的所有約定。如您是法律上之無行為能力人或限制行為能力人(如未滿二十歲之未成年人),則您在加入會員前,請將本服務條款交由您的法定代理人(如父母、輔助人或監護人)閱讀,並得到其同意,您才可註冊及使用 希平方學英文 所提供之會員服務。當您開始使用 希平方學英文 所提供之會員服務時,則表示您的法定代理人(如父母、輔助人或監護人)已經閱讀、了解並同意本服務條款。 我們可能會修改本條款或適用於本服務之任何額外條款,以(例如)反映法律之變更或本服務之變動。您應定期查閱本條款內容。這些條款如有修訂,我們會在本網頁發佈通知。變更不會回溯適用,並將於公布變更起十四天或更長時間後方始生效。不過,針對本服務新功能的變更,或基於法律理由而為之變更,將立即生效。如果您不同意本服務之修訂條款,則請停止使用該本服務。

第三人網站的連結 本服務或協力廠商可能會提供連結至其他網站或網路資源的連結。您可能會因此連結至其他業者經營的網站,但不表示希平方學英文與該等業者有任何關係。其他業者經營的網站均由各該業者自行負責,不屬希平方學英文控制及負責範圍之內。

兒童及青少年之保護 兒童及青少年上網已經成為無可避免之趨勢,使用網際網路獲取知識更可以培養子女的成熟度與競爭能力。然而網路上的確存有不適宜兒童及青少年接受的訊息,例如色情與暴力的訊息,兒童及青少年有可能因此受到心靈與肉體上的傷害。因此,為確保兒童及青少年使用網路的安全,並避免隱私權受到侵犯,家長(或監護人)應先檢閱各該網站是否有保護個人資料的「隱私權政策」,再決定是否同意提出相關的個人資料;並應持續叮嚀兒童及青少年不可洩漏自己或家人的任何資料(包括姓名、地址、電話、電子郵件信箱、照片、信用卡號等)給任何人。

為了維護 希平方學英文 網站安全,我們需要您的協助:

您承諾絕不為任何非法目的或以任何非法方式使用本服務,並承諾遵守中華民國相關法規及一切使用網際網路之國際慣例。您若係中華民國以外之使用者,並同意遵守所屬國家或地域之法令。您同意並保證不得利用本服務從事侵害他人權益或違法之行為,包括但不限於:
A. 侵害他人名譽、隱私權、營業秘密、商標權、著作權、專利權、其他智慧財產權及其他權利;
B. 違反依法律或契約所應負之保密義務;
C. 冒用他人名義使用本服務;
D. 上載、張貼、傳輸或散佈任何含有電腦病毒或任何對電腦軟、硬體產生中斷、破壞或限制功能之程式碼之資料;
E. 干擾或中斷本服務或伺服器或連結本服務之網路,或不遵守連結至本服務之相關需求、程序、政策或規則等,包括但不限於:使用任何設備、軟體或刻意規避看 希平方學英文 - 看 YouTube 學英文 之排除自動搜尋之標頭 (robot exclusion headers);

服務中斷或暫停
本公司將以合理之方式及技術,維護會員服務之正常運作,但有時仍會有無法預期的因素導致服務中斷或故障等現象,可能將造成您使用上的不便、資料喪失、錯誤、遭人篡改或其他經濟上損失等情形。建議您於使用本服務時宜自行採取防護措施。 希平方學英文 對於您因使用(或無法使用)本服務而造成的損害,除故意或重大過失外,不負任何賠償責任。

版權宣告
上次更新日期:2013-09-16

希平方學英文 內所有資料之著作權、所有權與智慧財產權,包括翻譯內容、程式與軟體均為 希平方學英文 所有,須經希平方學英文同意合法才得以使用。
希平方學英文歡迎你分享網站連結、單字、片語、佳句,使用時須標明出處,並遵守下列原則:

  • 禁止用於獲取個人或團體利益,或從事未經 希平方學英文 事前授權的商業行為
  • 禁止用於政黨或政治宣傳,或暗示有支持某位候選人
  • 禁止用於非希平方學英文認可的產品或政策建議
  • 禁止公佈或傳送任何誹謗、侮辱、具威脅性、攻擊性、不雅、猥褻、不實、色情、暴力、違反公共秩序或善良風俗或其他不法之文字、圖片或任何形式的檔案
  • 禁止侵害或毀損希平方學英文或他人名譽、隱私權、營業秘密、商標權、著作權、專利權、其他智慧財產權及其他權利、違反法律或契約所應付支保密義務
  • 嚴禁謊稱希平方學英文辦公室、職員、代理人或發言人的言論背書,或作為募款的用途

網站連結
歡迎您分享 希平方學英文 網站連結,與您的朋友一起學習英文。

抱歉傳送失敗!

不明原因問題造成傳送失敗,請儘速與我們聯繫!
希平方 x ICRT

「Tim Berners-Lee:下一代網路」- The next Web of open, linked data

觀看次數:2174  • 

框選或點兩下字幕可以直接查字典喔!

Time flies. It's actually almost 20 years ago when I wanted to reframe the way we use information, the way we work together: I invented the World Wide Web. Now, 20 years on, at TED, I want to ask your help in a new reframing.

So going back to 1989, I wrote a memo suggesting the global hypertext system. Nobody really did anything with it, pretty much. But 18 months later—this is how innovation happens—18 months later, my boss said I could do it on the side, as a sort of a play project, kick the tires of a new computer we'd got. And so he gave me the time to code it up. So I basically roughed out what HTML should look like: hypertext protocol, HTTP; the idea of URLs, these names for things which started with HTTP. I wrote the code and put it out there.

Why did I do it? Well, it was basically frustration. I was frustrated—I was working as a software engineer in this huge, very exciting lab, lots of people coming from all over the world. They brought all sorts of different computers with them. They had all sorts of different data formats, all sorts, all kinds of documentation systems. So that, in all that diversity, if I wanted to figure out how to build something out of a bit of this and a bit of this, everything I looked into, I had to connect to some new machine, I had to learn to run some new program, I would find the information I wanted in some new data format. And these were all incompatible. It was just very frustrating. The frustration was all this unlocked potential.

In fact, on all these discs there were documents. So if you just imagined them all being part of some big, virtual documentation system in the sky, say on the Internet, then life would be so much easier. Well, once you've had an idea like that it kind of gets under your skin and even if people don't read your memo—actually he did, it was found after he died, his copy. He had written, "Vague, but exciting," in pencil, in the corner.

But in general it was difficult—it was really difficult to explain what the web was like. It's difficult to explain to people now that it was difficult then. But then—OK, when TED started, there was no web so things like "click" didn't have the same meaning. I can show somebody a piece of hypertext, a page which has got links, and we click on the link and bing—there'll be another hypertext page. Not impressive. You know, we've seen that—we've got things on hypertext on CD-ROMs. What was difficult was to get them to imagine: so, imagine that that link could have gone to virtually any document you could imagine. Alright, that is the leap that was very difficult for people to make. Well, some people did. So yeah, it was difficult to explain, but there was a grassroots movement. And that is what has made it most fun. That has been the most exciting thing, not the technology, not the things people have done with it, but actually the community, the spirit of all these people getting together, sending the emails. That's what it was like then.

Do you know what? It's funny, but right now it's kind of like that again. I asked everybody, more or less, to put their documents—I said, "Could you put your documents on this web thing?" And you did. Thanks. It's been a blast, hasn't it? I mean, it has been quite interesting because we've found out that the things that happen with the web really sort of blow us away. They're much more than we'd originally imagined when we put together the little, initial website that we started off with. Now, I want you to put your data on the web. Turns out that there is still huge unlocked potential. There is still a huge frustration that people have because we haven't got data on the web as data.

What do you mean, "data"? What's the difference—documents, data? Well, documents you read, OK? More or less, you read them, you can follow links from them, and that's it. Data—you can do all kinds of stuff with a computer. Who was here or has otherwise seen Hans Rosling's talk? One of the great—yes a lot of people have seen it—one of the great TED Talks. Hans put up this presentation in which he showed, for various different countries, in various different colors—he showed income levels on one axis and he showed infant mortality, and he shot this thing animated through time. So, he'd taken this data and made a presentation which just shattered a lot of myths that people had about the economics in the developing world.

He put up a slide a little bit like this. It had underground all the data OK, data is brown and boxy and boring, and that's how we think of it, isn't it? Because data you can't naturally use by itself. But in fact, data drives a huge amount of what happens in our lives and it happens because somebody takes that data and does something with it. In this case, Hans had put the data together he had found from all kinds of United Nations websites and things. He had put it together, combined it into something more interesting than the original pieces and then he'd put it into this software, which I think his son developed, originally, and produces this wonderful presentation. And Hans made a point of saying, "Look, it's really important to have a lot of data." And I was happy to see that at the party last night that he was still saying, very forcibly, "It's really important to have a lot of data."

So I want us now to think about not just two pieces of data being connected, or six like he did, but I want to think about a world where everybody has put data on the web and so virtually everything you can imagine is on the web and then calling that linked data. The technology is linked data, and it's extremely simple. If you want to put something on the web there are three rules: first thing is that those HTTP names—those things that start with "http:"—we're using them not just for documents now, we're using them for things that the documents are about. We're using them for people, we're using them for places, we're using them for your products, we're using them for events. All kinds of conceptual things, they have names now that start with HTTP.

Second rule, if I take one of these HTTP names and I look it up and I do the web thing with it and I fetch the data using the HTTP protocol from the web, I will get back some data in a standard format which is kind of useful data that somebody might like to know about that thing, about that event. Who's at the event? Whatever it is about that person, where they were born, things like that. So the second rule is I get important information back.

Third rule is that when I get back that information it's not just got somebody's height and weight and when they were born, it's got relationships. Data is relationships. Interestingly, data is relationships. This person was born in Berlin; Berlin is in Germany. And when it has relationships, whenever it expresses a relationship then the other thing that it's related to is given one of those names that starts HTTP. So, I can go ahead and look that thing up. So I look up a person—I can look up then the city where they were born; then I can look up the region it's in, and the town it's in, and the population of it, and so on. So I can browse this stuff.

So that's it, really. That is linked data. I wrote an article entitled "Linked Data" a couple of years ago and soon after that, things started to happen. The idea of linked data is that we get lots and lots and lots of these boxes that Hans had, and we get lots and lots and lots of things sprouting. It's not just a whole lot of other plants. It's not just a root supplying a plant, but for each of those plants, whatever it is—a presentation, an analysis, somebody's looking for patterns in the data—they get to look at all the data and they get it connected together, and the really important thing about data is the more things you have to connect together, the more powerful it is.

So, linked data. The meme went out there. And, pretty soon Chris Bizer at the Freie Universitat in Berlin who was one of the first people to put interesting things up, he noticed that Wikipedia—you know Wikipedia, the online encyclopedia with lots and lots of interesting documents in it. Well, in those documents, there are little squares, little boxes. And in most information boxes, there's data. So he wrote a program to take the data, extract it from Wikipedia, and put it into a blob of linked data on the web, which he called dbpedia. Dbpedia is represented by the blue blob in the middle of this slide and if you actually go and look up Berlin, you'll find that there are other blobs of data which also have stuff about Berlin, and they're linked together. So if you pull the data from dbpedia about Berlin, you'll end up pulling up these other things as well. And the exciting thing is it's starting to grow. This is just the grassroots stuff again, OK?

Let's think about data for a bit. Data comes in fact in lots and lots of different forms. Think of the diversity of the web. It's a really important thing that the web allows you to put all kinds of data up there. So it is with data. I could talk about all kinds of data. We could talk about government data, enterprise data is really important, there's scientific data, there's personal data, there's weather data, there's data about events, there's data about talks, and there's news and there's all kinds of stuff. I'm just going to mention a few of them so that you get the idea of the diversity of it, so that you also see how much unlocked potential.

Let's start with government data. Barack Obama said in a speech, that he—American government data would be available on the Internet in accessible formats. And I hope that they will put it up as linked data. That's important. Why is it important? Not just for transparency, yeah transparency in government is important, but that data—this is the data from all the government departments. Think about how much of that data is about how life is lived in America. It's actual useful. It's got value. I can use it in my company. I could use it as a kid to do my homework. So we're talking about making the place, making the world run better by making this data available.

In fact if you're responsible—if you know about some data in a government department, often you find that these people, they're very tempted to keep it—Hans calls it database hugging. You hug your database, you don't want to let it go until you've made a beautiful website for it. Well, I'd like to suggest that rather—yes, make a beautiful website, who am I to say don't make a beautiful website? Make a beautiful website, but first give us the unadulterated data, we want the data. We want unadulterated data. OK, we have to ask for raw data now. And I'm going to ask you to practice that, OK? Can you say "raw"?

Audience: Raw.

Tim Berners-Lee: Can you say "data"?

Audience: Data.

TBL: Can you say "now"?

Audience: Now!

TBL: Alright, "raw data now"!

Audience: Raw data now!

Practice that. It's important because you have no idea the number of excuses people come up with to hang onto their data and not give it to you, even though you've paid for it as a taxpayer. And it's not just America. It's all over the world. And it's not just governments, of course—it's enterprises as well.

So I'm just going to mention a few other thoughts on data. Here we are at TED, and all the time we are very conscious of the huge challenges that human society has right now—curing cancer, understanding the brain for Alzheimer's, understanding the economy to make it a little bit more stable, understanding how the world works. The people who are going to solve those—the scientists—they have half-formed ideas in their head, they try to communicate those over the web. But a lot of the state of knowledge of the human race at the moment is on databases, often sitting in their computers, and actually, currently not shared.

In fact, I'll just go into one area—if you're looking at Alzheimer's, for example, drug discovery—there is a whole lot of linked data which is just coming out because scientists in that field realize this is a great way of getting out of those silos, because they had their genomics data in one database in one building, and they had their protein data in another. Now, they are sticking it onto—linked data—and now they can ask the sort of question, that you probably wouldn't ask, I wouldn't ask—they would. What proteins are involved in signal transduction and also related to pyramidal neurons? Well, you take that mouthful and you put it into Google. Of course, there's no page on the web which has answered that question because nobody has asked that question before. You get 223,000 hits—no results you can use. You ask the linked data—which they've now put together—32 hits, each of which is a protein which has those properties and you can look at. The power of being able to ask those questions, as a scientist—questions which actually bridge across different disciplines—is really a complete sea change. It's very very important. Scientists are totally stymied at the moment—the power of the data that other scientists have collected is locked up and we need to get it unlocked so we can tackle those huge problems.

Now if I go on like this, you'll think that all the data comes from huge institutions and has nothing to do with you. But, that's not true. In fact, data is about our lives. You just—you log on to your social networking site, your favorite one, you say, "This is my friend."Bing! Relationship. Data. You say, "This photograph, it's about—it depicts this person." Bing! That's data. Data, data, data. Every time you do things on the social networking site, the social networking site is taking data and using it—re-purposing it—and using it to make other people's lives more interesting on the site. But, when you go to another linked data site—and let's say this is one about travel, and you say, "I want to send this photo to all the people in that group," you can't get over the walls. The Economist wrote an article about it, and lots of people have blogged about it—tremendous frustration. The way to break down the silos is to get inter-operability between social networking sites. We need to do that with linked data.

One last type of data I'll talk about, maybe it's the most exciting. Before I came down here, I looked it up on OpenStreetMap. The OpenStreetMap's a map, but it's also a Wiki. Zoom in and that square thing is a theater—which we're in right now—The Terrace Theater. It didn't have a name on it. So I could go into edit mode, I could select the theater, I could add down at the bottom the name, and I could save it back. And now if you go back to the OpenStreetMap. org, and you find this place, you will find that The Terrace Theater has got a name. I did that. Me! I did that to the map. I just did that! I put that up on there. Hey, you know what? If I—that street map is all about everybody doing their bit and it creates an incredible resource because everybody else does theirs. And that is what linked data is all about. It's about people doing their bit to produce a little bit, and it all connecting. That's how linked data works. You do your bit. Everybody else does theirs. You may not have lots of data which you have yourself to put on there but you know to demand it. And we've practiced that.

So, linked data—it's huge. I've only told you a very small number of things. There are data in every aspect of our lives, every aspect of work and pleasure, and it's not just about the number of places where data comes, it's about connecting it together. And when you connect data together, you get power in a way that doesn't happen just with the web, with documents. You get this really huge power out of it. So, we're at the stage now where we have to do this—the people who think it's a great idea. And all the people—and I think there's a lot of people at TED who do things because—even though there's not an immediate return on the investment because it will only really pay off when everybody else has done it—they'll do it because they're the sort of person who just does things which would be good if everybody else did them. OK, so it's called linked data. I want you to make it. I want you to demand it. And I think it's an idea worth spreading.

Thanks.

播放本句

登入使用學習功能

使用Email登入

HOPE English 播放器使用小提示

  • 功能簡介

    單句重覆、重複上一句、重複下一句:以句子為單位重覆播放,單句重覆鍵顯示綠色時為重覆播放狀態;顯示白色時為正常播放狀態。按重複上一句、重複下一句時就會自動重覆播放該句。
    收錄佳句:點擊可增減想收藏的句子。

    中、英文字幕開關:中、英文字幕按鍵為綠色為開啟,灰色為關閉。鼓勵大家搞懂每一句的內容以後,關上字幕聽聽看,會發現自己好像在聽中文說故事一樣,會很有成就感喔!
    收錄單字:框選英文單字可以收藏不會的單字。
  • 分享
    如果您有收錄很優秀的句子時,可以分享佳句給大家,一同看佳句學英文!