Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
情報社会論2018 #09 "GitHub"
Search
Taichi FURUHASHI
June 19, 2018
Education
0
160
情報社会論2018 #09 "GitHub"
青山学院大学 AOYAMAスタンダード(教養)
「情報社会論」講義資料
#AGU情報社会論
© mapconcierge, CC BY-SA 4.0
Taichi FURUHASHI
June 19, 2018
Tweet
Share
More Decks by Taichi FURUHASHI
See All by Taichi FURUHASHI
20201127_ジオ展2020_古橋
mapconcierge
0
180
20201126_お茶の水女子大学環境地理学基礎演習02
mapconcierge
0
160
20201119_お茶の水女子大学環境地理学基礎演習01
mapconcierge
1
190
ICT東京フォーラム2020「災害におけるドローンの活用」古橋
mapconcierge
0
310
The Past, Present, and Future of OpenStreetMap Japan 〜 一億総伊能化は実現できるのか 〜
mapconcierge
0
190
オンライン授業前提社会におけるGIS教育手法の検討と実践
mapconcierge
0
100
青学 地球共生学2020 古橋担当回
mapconcierge
0
110
情報社会論 #11
mapconcierge
0
200
20200708_GSC_地球共生学_lite.pdf
mapconcierge
0
510
Other Decks in Education
See All in Education
0121
cbtlibrary
0
120
React完全入門
mickey_kubo
1
110
Cifrado asimétrico
irocho
0
380
AIでキミの未来はどう変わる?
behomazn
0
110
外国籍エンジニアの挑戦・新卒半年後、気づきと成長の物語
hypebeans
0
730
1014
cbtlibrary
0
530
【dip】「なりたい自分」に近づくための、「自分と向き合う」小さな振り返り
dip_tech
PRO
0
230
KBS新事業創造体験2025_科目説明会
yasuchikawakayama
0
160
心理学を学び活用することで偉大なスクラムマスターを目指す − 大学とコミュニティを組み合わせた学びの循環 / Becoming a great Scrum Master by learning and using psychology
psj59129
1
1.7k
HyRead2526
cbtlibrary
0
200
Adobe Express
matleenalaakso
2
8.1k
Web 2.0 Patterns and Technologies - Lecture 8 - Web Technologies (1019888BNR)
signer
PRO
0
3k
Featured
See All Featured
XXLCSS - How to scale CSS and keep your sanity
sugarenia
249
1.3M
Rails Girls Zürich Keynote
gr2m
96
14k
What’s in a name? Adding method to the madness
productmarketing
PRO
24
3.9k
The Curse of the Amulet
leimatthew05
1
8.7k
Have SEOs Ruined the Internet? - User Awareness of SEO in 2025
akashhashmi
0
270
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
21
1.4k
Leo the Paperboy
mayatellez
4
1.4k
Chasing Engaging Ingredients in Design
codingconduct
0
110
The AI Revolution Will Not Be Monopolized: How open-source beats economies of scale, even for LLMs
inesmontani
PRO
3
3k
Designing for humans not robots
tammielis
254
26k
Build The Right Thing And Hit Your Dates
maggiecrowley
39
3k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
32
2.8k
Transcript
੨ࢁֶӃେֶٿࣾձڞੜֶ෦ ݹڮେ !NBQDPODJFSHF ใࣾձ
ຊίϯςϯπͷ ϥΠηϯεಛʹஅΓͷͳ͍ݶΓ $$#:4"ʹै͍·͢ɻ
ઌʑिͷ՝ ʮ(PPHMFϚοϓɾ(PPHMF&BSUIʯΛ༻͍ͯɺ ݕࡧ݁ՌਤߤۭࣸਅΛࢀߟʹ ล͓͢͢ΊΧϑΣΨΠυϚοϓΛ࡞ɻ ͦͷίϯςϯπΛΣϒ্Ͱެ։͠ɺ ୭ͰӾཡՄೳʹ͍ͨ͠ͱߟ͑ͨɻ ຊࠃʹ͓͍ͯɺϑΣΞϢʔεͷ؍Ͱ ͜ͷΑ͏ͳߦҝΛֶੜ͕ߦͬͨ߹ ͲͷΑ͏ͳ͕ى͜Δ͔จࣈҎͰ ࣗͷҙݟΛ͡Αɻ
"(6ใࣾձͷϋογϡλάΛؚΊ͍ͯͩ͘͞ɻ
ώϯτ
(PPHMFϚοϓ&BSUI ར༻ن܈ (PPHMFϚοϓ(PPHMF&BSUIʹΞΫηεɺ(PPHMFϚοϓ(PPHMF&BSUIͷΞϓϦΛμϯϩʔυ·ͨ༻͢Δ͜ͱͰɺ࣍ʹ ಉҙͨ͠ͷͱ͠·͢ɻ (PPHMFར༻نʢҎԼʮڞ௨ར༻نʯʣɺ (PPHMFϚοϓ(PPHMF&BSUIՃنʢҎԼɺʮϚοϓ&BSUIՃنʯʣɺ (PPHMFϚοϓ(PPHMF&BSUI๏త௨ʢҎԼʮ๏త௨ʯʣɺ͓Αͼ (PPHMFϓϥΠόγʔϙϦγʔʢҎԼʮϓϥΠόγʔϙϦγʔʯʣɻ ͜ΕΒͭͷจॻΛҙਂ͓͘ಡΈ͍ͩ͘͞ɻ·ͣڞ௨ར༻نΛ͓ಡΈ͍ͩ͘͞ɻڞ௨ར༻نͰɺΞοϓϩʔυͨ͠ί ϯςϯπͷతॴ༗ݖɺ͓Αͼ(PPHMFίϯςϯπୈࡾऀͷίϯςϯπͷ༻·ͨӡసதͷ(PPHMFϚοϓ(PPHMF&BSUI
ͷ༻ʹ͓͚Δ͓٬༷ͷͳͲʹ͍ͭͯ໌Β͔ʹ͍ͯ͠·͢ɻ ڞ௨نɺϚοϓ&BSUIͷՃنɺ๏త௨ɺ͓ΑͼϓϥΠόγʔϙϦγʔΛʮܖʯͱ૯শ͠·͢ɻ͜ͷܖɺ(PPHMF Ϛοϓ(PPHMF&BSUIͷ༻ʹؔͯ͠ɺ͓٬༷ͱ(PPHMFؒͰ๏త߆ଋྗΛ࣋ͪ·͢ɻ IUUQTXXXHPPHMFDPNJOUMKBIFMQUFSNT@NBQTIUNM
(PPHMFϚοϓ(PPHMF&BSUI Ճར༻ن ېࢭߦҝɻ(PPHMFϚοϓ(PPHMF&BSUIͷ༻࣌ʹ࣍ͷߦҝېࢭ͞Ε͍ͯ·͢ʢ͓٬༷ͷཧਓ͕ߦ͏͜ͱېࢭ͞Ε͍ͯ·͢ʣɻ B(PPHMFϚοϓ(PPHMF&BSUIͷҰ෦Λ࠶·ͨൢച͢Δ͜ͱɺ(PPHMFϚοϓ(PPHMF&BSUIʹج͍ͮͯ৽͍͠αʔϏεΛ࡞͢Δ͜ ͱʢར༻نʹै͏(PPHMFϚοϓ(PPHMF&BSUIͷ"1*༻Λআ͘ʣɺ CίϯςϯπΛίϐʔ͢Δ͜ͱʢ(PPHMFϚοϓɺ(PPHMF&BSUIɺετϦʔτϏϡʔͷ༻ڐϖʔδ·ͨʮϑΣΞϢʔεʯΛؚΉతॴ༗ݖʹద ༻͞ΕΔ๏ͰڐՄ͞Ε͍ͯΔ߹Λআ͘ʣɺ DίϯςϯπΛେྔμϯϩʔυ·ͨҰׅϑΟʔυΛ࡞͢Δ͜ͱʢ·ͨͦͷߦҝΛୈࡾऀʹҕୗ͢Δ͜ͱʣɺ E(PPHMFϚοϓ(PPHMF&BSUIΛ༻ͯ͠ਤؔ࿈ͷผͷσʔληοτʢਤφϏήʔγϣϯͷσʔληοτɺϏδωεϦεςΟϯάͷσʔλ ϕʔεɺϝʔϦϯάϦετɺςϨϚʔέςΟϯάϦετΛؚΉʣΛɺ(PPHMFϚοϓ(PPHMF&BSUIʹΘΔ·ͨͦΕʹྨࣅ͢ΔαʔϏεͰ༻
͢ΔతͰ࡞͢Δ͜ͱɺ F(PPHMFϚοϓ(PPHMF&BSUIΛୈࡾऀͷαʔϏεͰɺ·ͨϦΞϧλΠϜφϏήʔγϣϯࣗతं੍྆ޚʹؔ࿈ͯ͠༻͢Δ͜ͱ ʢ"OESPJE"VUP4FOEUP$BSͳͲ(PPHMF͕ఏڙ͢ΔػೳΛհ͢Δ߹Λআ͘ʣɺ G(PPHMFϚοϓ(PPHMF&BSUI·ͨͦͷؔ࿈ιϑτΣΞͷιʔείʔυͷϦόʔεΤϯδχΞϦϯάநग़Λߦ͏͜ͱʢͦͷΑ͏ͳ੍ݶ͕๏ ʹΑͬͯېࢭ͞Ε͍ͯΔൣғΛআ͘ʣɺ H(PPHMFར༻نɺͦΕʹؚ·ΕΔϦϯΫऍɺ·ͨஶ࡞ݖɺඪɺͦͷଞͷॴ༗ݖʹ͍ͭͯͷهࡌΛআɺӅ͍ɺมߋ͢Δ͜ͱɺ·ͨ IୈࡾऀͷݖརʢϓϥΠόγʔݖɺύϒϦγςΟʔݖɺతॴ༗ݖΛؚΉʣʹର͢Δෆదɺҧ๏ͳߦҝ·ͨͦΕΛ৵͢Δߦҝɻ IUUQTXXXHPPHMFDPNJOUMKBIFMQUFSNT@NBQTIUNM
ϑΣΞϢʔε (PPHMF͔ΒϢʔβʔʹ༩͞ΕΔϥΠηϯεͱผʹɺϢʔβʔʮϑΣΞϢʔ εʯͷنఆʹج͍ͮͯ(PPHMFͷίϯςϯπΛ༻Ͱ͖·͢ɻϑΣΞϢʔεͱ ɺʮಛఆͷঢ়گʹ͓͍ͯɺஶ࡞ݖอ࣋ऀͷڐՄΛಘͳͯ͘ஶ࡞Λ༻Ͱ͖ Δʯͱ͢Δถࠃஶ࡞ݖ๏ͷߟ͑ํͰ͢ɻ ถࠃҎ֎ͷࠃͷஶ࡞ݖ๏ʹಉ༷ͷʢͨͩ͠ଟ͘ͷ߹ɺΑΓݶఆ͞Εͨʣ֓೦͕ ͋Γ·͢ɻͨͱ͑ɺଟ͘ͷࠃʹ͓͍ͯʮϑΣΞσΟʔϦϯάʯͱͯ͠ΒΕΔ֓ ೦͕͋Γ·͢ɻϢʔβʔ͕(PPHMFͷίϯςϯπΛ༻͢ΔࡍɺͦΕ͕ϑΣΞϢʔ εʹ͋ͨΔ͔Ͳ͏͔ɺ·ͨϑΣΞσΟʔϦϯάͱΈͳ͞ΕΔ͔Ͳ͏͔Λ(PPHMF அͰ͖·ͤΜɻ͜ΕΛஅ͢Δʹɺίϯςϯπͷ༻ʹؔ͢Δ۩ମతͳࣄ࣮
Λͯ͢౿·͑ͨ͏͑Ͱ๏తʹੳ͢Δඞཁ͕͋Γ·͢ɻஶ࡞ͷϑΣΞϢʔεʹ ؔ͢Δෆ໌ʹ͍ͭͯหޢ࢜ʹ૬ஊ͢Δ͜ͱΛ͓͢͢Ί͠·͢ɻ IUUQTXXXHPPHMFDPKQJOUMKBQFSNJTTJPOTHFPHVJEFMJOFTIUNM (PPHMFϚοϓɺ(PPHMF&BSUIɺετϦʔτϏϡʔͷ༻
IUUQXXXQSFGLVNBNPUPKQLJKJ@IUNM
IUUQXXXQSFGLVNBNPUPKQDPNNPO6QMPBE'JMF0VUQVUBTIY D@JEJETVC@JEqJE
IUUQXXXQSFGLVNBNPUPKQDPNNPO6QMPBE'JMF0VUQVUBTIY D@JEJETVC@JEqJE ๏ ଌྔ๏ɺਫ࿏ۀ๏ Λ Βͳ͍ެһͷ࣮ଶ
IUUQXXXQSFGLVNBNPUPKQDPNNPO6QMPBE'JMF0VUQVUBTIY D@JEJETVC@JEqJE ग़ॲෆ໌ͷࢿྉΛ҆қʹ͏ެһͷ࣮ଶ
IUUQXXXQSFGLVNBNPUPKQDPNNPO6QMPBE'JMF0VUQVUBTIY D@JEJETVC@JEqJE ར༻نΛಡ·ͳ͍ެһͷ࣮ଶ
IUUQXXXQSFGLVNBNPUPKQDPNNPO6QMPBE'JMF0VUQVUBTIY D@JEJETVC@JEqJE άʔάϧθϯϦϯͰͳ͍ͱ ޡղ͍ͯ͠Δެһͷ࣮ଶ
࠷ۙͷ
ήϯίϥ
IUUQTUXJUUFSDPNOFX@NBSVTUBUVT
IUUQTXXXDIPVCVOTIBDPNOFXTOFXTQIQ
ࠓͷςʔϚ
୭͕ɺͲ͏ɺ ೋ࣍ར༻͍ͯ͠Δ͔ʁ
5SBDFBCJMJUZ τ Ϩ ʔ α Ϗ Ϧ ς Ο
None
(JU)VC
IUUQTHJUIVCTBUFMMJUFDPN
ੈքͰ࠷ Φʔϓϯͳ ৫ʁ
None
None
IUUQTUXJUUFSDPNJUNFEJB@OFXTTUBUVT
None
4PDJBM$PEJOH
'PSL
IUUQTXXXHPPHMFDPKQTFBSDI RGPSLTPVSDFMONTUCNJTDITB9WFEBI6,&XKF0GUO6"I8&(;2,);9#U.2@"6*$JH#CJXCJI
“Phylogenetic tree” IUUQTFOXJLJQFEJBPSHXJLJ1IZMPHFOFUJD@USFF 8JLJQFEJB $$#:4"
3FQPTJUPSZ
Fork
Pull Request Merge
Merge
None
5SBDFBCJMJUZ
'PSL͞Εͨઌ͕ ḷΕΔɻ
IUUQTHJUIVCDPNHTDBPZBNB)PX5P.BLF'SFF$VMUVSFOFUXPSL
IUUQTHJUIVCDPNNUPZPEBTMOFUXPSL
ϥΠηϯε ఆٛՄೳɻ
None
ࠓिͷ՝ (JU)VCΛ༻͍ͯɺ ৽نʹެ։ϦϙδτϦΛ࡞͠ɺ ͦͷϦϙδτϦͷιϑτΣΞϥΠηϯεΛɺ .*5-JDFOTFͱͯ͠ઃఆɻ $0%&ͱͯ͠ IUUQTHJUIVCDPNNBQDPODJFSHFTMDNE ΛࢀߟʹTMDNECBTIϑΝΠϧΛ࡞ɻ ϦϙδτϦͷ1FSNBMJOLΛ 5XJUUFSʹߘ͍ͯͩ͘͠͞ɻ
"(6ใࣾձͷϋογϡλάΛؚΊ͍ͯͩ͘͞ɻ
ͳͥɺ (JU)VCʹ $SFBUJWF$PNNPOT ϥΠηϯε͕ ඪ४Ͱબͳ͍ʁ
ੲ $$͕બ͚ͨͲ ࠓϦετ͔Β আ͞Εͨɻ
͓·͚
TMίϚϯυ
δϣʔΫίϚϯυ
6/*9Ͱ MTίϚϯυ͕ඞਢ
ॳ৺ऀ MTΛTMʹ ଧͪؒҧ͍ଟൃ
TMB
IUUQTHJUIVCDPNNUPZPEBTM
ϥΠηϯεʁ
IUUQTHJUIVCDPNNUPZPEBTMCMPCNBTUFS-*$&/4& ࣮࣭$$#:తΦϨΦϨϥΠηϯεɻ
̍ͰͰ͖Δ 4-ίϚϯυ Πϯετʔϧํ๏ ʢಈըฤʣ
IUUQTZPVUVCF",K1'8FBI*